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NASA NTRS2024

Baltimore Energy & Infrastructure: Assessing Urban Heat Vulnerability in Baltimore Neighborhoods to Inform Transportation Resiliency Planning Efforts

Across the world, climate change is altering cities and their local climate systems. Following global trends of rising mean temperatures, Baltimore, Maryland is projected to experience more frequent extreme heat events. Exacerbated by Urban Heat Island (UHI) effects, residents of the city face high temperatures from limited tree canopy, highly paved and impervious surfaces, limited air flow, and high concentrations of localized emissions. Urban heat is dispersed asymmetrically, with historically marginalized populations experiencing disproportionately severe heat. Recognizing the impacts of extreme urban heat, the Maryland Transit Administration (MTA) collaborated with us, the Spring 2024 Goddard Energy and Infrastructure NASA DEVELOP team to assess urban impacts of MTA users and assets and explore opportunities to enhance resiliency planning. We evaluated the feasibility of NASA Earth observations (EOs) in visualizing heat vulnerability in Baltimore City and County. We mapped UHI and extreme heat using remote sensing observations, tailored a Heat Priority Score (HPS) to analyze heat data in tandem with socioeconomic data from American Community Survey (ACS), and utilized SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model to estimate MTA riders’ thermal comfort. NASA EOs served to quantify the distribution and severity of extreme heat at the block group level, which was found to correlate with a lack of vegetation and presence of densely built-up surroundings. The HPS revealed that extreme heat events most negatively impact communities that exhibit social vulnerability through indicators such as age, race, and income. These findings will inform neighborhood resiliency plans for the MTA that can be incorporated into their Adaptation Resiliency Toolbox (ART).

Baltimore,↗
NASA NTRS2022

Evolution and folding of repeat proteins

Repeat proteins are made with tandem copies of similar amino acid stretches that fold into elongated architectures. These proteins constitute excellent model systems to investigate how evolution relates to structure, folding, and function. Here, we propose a scheme to map evolutionary information at the sequence level to a coarse-grained model for repeat-protein folding and use it to investigate the folding of thousands of repeat proteins. We model the energetics by a combination of an inverse Potts-model scheme with an explicit mechanistic model of duplications and deletions of repeats to calculate the evolutionary parameters of the system at the single-residue level. These parameters are used to inform an Ising-like model that allows for the generation of folding curves, apparent domain emergence, and occupation of intermediate states that are highly compatible with experimental data in specific case studies. We analyzed the folding of thousands of natural Ankyrin repeat proteins and found that a multiplicity of folding mechanisms are possible. Fully cooperative all-or-none transitions are obtained for arrays with enough sequence-similar elements and strong interactions between them, while noncooperative element-by-element intermittent folding arose if the elements are dissimilar and the interactions between them are energetically weak. Additionally, we characterized nucleation-propagation and multidomain folding mechanisms. We show that the global stability and cooperativity of the repeating arrays can be predicted from simple sequence scores.

Ezequiel A. Galpern↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are bands of upper-level clouds regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle. However, these hypothesized relationships have not been rigorously tested due to the subjective nature of TCBs in satellite images. A machine learning technique that successfully identifies TCBs objectively in imagery from the GOES-16 Advanced Baseline Imager (ABI) has been developed to solve this problem. The technique uses a U-Net convolutional neural network (CNN) that assigns a probability to each pixel in an image based on the likelihood of the pixel being associated with a TCB. Using the U-Net CNN, a database of TCBs from 2019 to 2022 was developed for the Atlantic tropical cyclone basin by defining an appropriate probability threshold that defines the difference between TCB and non-TCB pixels. This threshold is where the Jaccard score, calculated using manually identified TCBs and model identified TCBs, is maximized. Statistics for TCB occurrence will also be presented, including the relationships between TCBs and storm relative motion, shear relative direction, cardinal direction, tropical cyclone intensity, tropical cyclone intensification rates, and time of day.

John Mark Mayhall↗
NASA NTRS1991

Resolving Sensory Conflict: the Effect of Muscle Vibration on Postural Stability

The otolith-tilt reinterpretation hypothesis (OTTR) proposes that the central nervous system adapts to weightlessness by reinterpreting all otolith input as linear motion. While interpreting otolith input exclusively as linear motion is functionally useful in space, it is maladaptive upon return to Earth. Astronauts have reported experiencing illusory sensations during head movement which contributes to postural instability. The effect is assessed of muscle vibration in combination with a variety of sensory conflicts on postural equilibrium. The equilibrium of six healthy subjects was tested using the EquiTest sensory test protocol, with and without the confounding influence of triceps surea vibration. The data were analyzed with repeated measures with vibration, vision status, and platform status as independent variables. All main effects and an interaction between the presence of vision and platform sway referencing were found to be significant. Overall, a 4.5 pct. decrease in postural stability was observed with vibration. The trend of the difference scores between conditions with and without vibration suggests that vibration is most destabilizing when the triceps surea is able to change length during postural sway (i.e., conditions with a fixed support surface). The impact of sway referencing vision was virtually identical to that of eye closure, providing compelling evidence that sway referencing 'nulls out' useful cues about subject sway.

Layne, Charles S.↗
NASA NTRS2002

Investigation and Development of Data-Driven D-Region Model for HF Systems Impacts

Space Environment Corporation (SEC) and RP Consultants (RPC) are to develop and validate a weather-capable D region model for making High Frequency (HF) absorption predictions in support of the HF communications and radar communities. The weather-capable model will assimilate solar and earth space observations from NASA satellites. The model will account for solar-induced impacts on HF absorption, including X-rays, Solar Proton Events (SPE's), and auroral precipitation. The work plan includes: I . Optimize D-region model to quickly obtain ion and electron densities for proper HF absorption calculations. 2. Develop indices-driven modules for D-region ionization sources for low, mid, & high latitudes including X-rays, cosmic rays, auroral precipitation, & solar protons. (Note: solar spectrum & auroral modules already exist). 3. Setup low-cost monitors of existing HF beacons and add one single-frequency beacon. 4. Use PENEX HF-link database with HF monitor data to validate D-region/HF absorption model using climatological ionization drivers. 5. Develop algorithms to assimilate NASA satellite data of solar, interplanetary, and auroral observations into ionization source modules. 6. Use PENEX HF-link & HF-beacon data for skill score comparison of assimilation versus climatological D-region/HF absorption model. Only some satellites are available for the PENEX time period, thus, HF-beacon data is necessary. 7. Use HF beacon monitors to develop HF-link data assimilation algorithms for regional improvement to the D-region/HF absorption model.

Eccles, J. V.↗
NASA NTRS1996

Cellular and molecular analysis of mutagenesis induced by charged particles of defined linear energy transfer

Mutation induction by charged particles of defined linear energy transfer (LET) and gamma rays was scored using human-hamster hybrid AL cells. The LET values for charged particles accelerated at the Radiological Research Accelerator Facility ranged from 10 keV/microm protons to 150 keV/microm 4He ions. The induced mutant fractions at both the S1 and HGPRT loci were dependent on the dose and LET. In addition, for each dose examined, the mutant yield at the S1 locus was 30-60 fold higher than at the corresponding HGPRT locus. To determine whether the mutation spectrum was comparably dependent on dose and LET, independent S1- and HGPRT- mutants induced by 150 keV/microm 4He ions and gamma rays were isolated, and their DNA was analyzed by both Southern blotting and multiplex PCR methods. While the majority of radiation-induced mutants showed deletions of varying sizes, the relative percentage of large deletions was found to be related to both the dose and LET of the radiation examined. Using a mutation system that can detect multilocus changes, results of the present study show that radiation-induced chromosomal loss can be in the millions of base pairs.

NASA Discipline Radiation Health↗
NASA NTRS2013

Decadal Prediction Skill in the GEOS-5 Forecast System

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office's (GMAO's) GEOS-5 Atmosphere-Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multivariate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO's atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean Atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 percent improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the sub-polar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

Decadal Prediction↗
NASA NTRS1990

Evaluation of voice codecs for the Australian mobile satellite system

The evaluation procedure to choose a low bit rate voice coding algorithm is described for the Australian land mobile satellite system. The procedure is designed to assess both the inherent quality of the codec under 'normal' conditions and its robustness under 'severe' conditions. For the assessment, normal conditions were chosen to be random bit error rate with added background acoustic noise and the severe condition is designed to represent burst error conditions when mobile satellite channel suffers from signal fading due to roadside vegetation. The assessment is divided into two phases. First, a reduced set of conditions is used to determine a short list of candidate codecs for more extensive testing in the second phase. The first phase conditions include quality and robustness and codecs are ranked with a 60:40 weighting on the two. Second, the short listed codecs are assessed over a range of input voice levels, BERs, background noise conditions, and burst error distributions. Assessment is by subjective rating on a five level opinion scale and all results are then used to derive a weighted Mean Opinion Score using appropriate weights for each of the test conditions.

Bundrock, Tony↗
NASA NTRS2002

Phylogeny and systematic position of Opiliones: a combined analysis of chelicerate relationships using morphological and molecular data

The ordinal level phylogeny of the Arachnida and the suprafamilial level phylogeny of the Opiliones were studied on the basis of a combined analysis of 253 morphological characters, the complete sequence of the 18S rRNA gene, and the D3 region of the 28S rRNA gene. Molecular data were collected for 63 terminal taxa. Morphological data were collected for 35 exemplar taxa of Opiliones, but groundplans were applied to some of the remaining chelicerate groups. Six extinct terminals, including Paleozoic scorpions, are scored for morphological characters. The data were analyzed using strict parsimony for the morphological data matrix and via direct optimization for the molecular and combined data matrices. A sensitivity analysis of 15 parameter sets was undertaken, and character congruence was used as the optimality criterion to choose among competing hypotheses. The results obtained are unstable for the high-level chelicerate relationships (except for Tetrapulmonata, Pedipalpi, and Camarostomata), and the sister group of the Opiliones is not clearly established, although the monophyly of Dromopoda is supported under many parameter sets. However, the internal phylogeny of the Opiliones is robust to parameter choice and allows the discarding of previous hypotheses of opilionid phylogeny such as the "Cyphopalpatores" or "Palpatores." The topology obtained is congruent with the previous hypothesis of "Palpatores" paraphyly as follows: (Cyphophthalmi (Eupnoi (Dyspnoi + Laniatores))). Resolution within the Eupnoi, Dyspnoi, and Laniatores (the latter two united as Dyspnolaniatores nov.) is also stable to the superfamily level, permitting a new classification system for the Opiliones. c2002 The Willi Hennig Society.

NASA Discipline Evolutionary Biology↗
NASA NTRS2014

Contributions of Astronauts Aerobic Exercise Intensity and Time on Change in VO2peak during Spaceflight

There is considerable variability among astronauts with respect to changes in maximal aerobic capacity (VO2peak) during International Space Station (ISS) missions, ranging from a 5% increase to 30% decline. Individual differences may be due to in-flight aerobic exercise time and intensity. PURPOSE: To evaluate the effects of in-flight aerobic exercise time and intensity on change in VO2peak during ISS missions. METHODS: Astronauts (N=11) performed peak cycle tests approx 60 days before flight (L-60), on flight day (FD) approx 14, and every approx 30 days thereafter. Metabolic gas analysis and heart rate (HR) were measured continuously during the test using the portable pulmonary function system. HR and duration of each in-flight cycle ergometer and treadmill (TM) session were recorded and averaged in time segments corresponding to each peak test. Mixed effects linear regression with exercise mode (TM or cycle) as a categorical variable was used to assess the contributions of exercise intensity (%time >70% peak HR or %time >90% peak HR) and time (min/wk), adjusted for body weight, on %change in VO2peak during the mission, and incorporating the repeated-measures experimental design. RESULTS: 110 observations were included in the model (4-6 peak cycle tests per astronaut, 2 exercise devices). VO2peak was reduced from preflight throughout the mission (FD14: 13+/-13% and FD 105: 8+/-10%). Exercise intensity (%peak HR: FD14=66+/-14; FD105=75+/-8) and time (min/wk: FD14=82+/-46; FD105=158+/-40) increased during flight. The models showed main effects for exercise time and intensity with no interactions between time, intensity, and device (70% peak HR: time [z-score=2.39; P=0.017], intensity [z-score=3.51; P=0.000]; 90% peak HR: time [zscore= 3.31; P=0.001], intensity [z-score=2.24; P=0.025]). CONCLUSION: Exercise time and intensity independently contribute to %change in VO2peak during ISS missions, indicating that there are minimal values for exercise time and intensity required to maintain VO2peak. As the FD105 average exercise intensity and time did not prevent a decline in VO2peak from preflight, astronauts' exercise prescriptions should target at least 160 min of weekly aerobic exercise at an average above 75% peak HR with increased time at intensities above 90% of peak HR starting early in the mission.

Downs, Meghan E.↗
NASA NTRS2007

Artificial Gravity as a Multi-System Countermeasure: Effects on Cognitive Function

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is a medical requirement on the International Space Station, and its purpose is to evaluate cognitive functioning after physical insult (e.g., head trauma, decompression sickness, exposure to toxic gases, medication side effects). The current objective is to assess cognitive functioning in a long duration space mission analog environment where Artificial Gravity is being applied as a countermeasure in a Bed Rest study. Methods: Fifteen male subjects (8 treatment and 7 control) who participated in 21 days of -6 degree head-down bed rest were assessed. Three practice and three baseline WinSCAT test sessions were administered during the pre-bed rest phase of study participation. During the bed rest phase, the WinSCAT test was scheduled every other day, following the centrifuge, for a total of 10 test sessions. (The treatment group received 60 minutes of centrifugation each day during the 21 days of bed rest. The control subjects were strapped to the centrifuge for the same length of time as the treatment group but were not spun.) During the post-bed rest (reconditioning) phase, the test was administered 4 times. Results: Individual differences were found both within and between the treatment and control groups. After controlling for the number of subjects in each group, the treatment group accounted for more off-nominal WinSCAT scores than the control group. Conclusions:There is some preliminary evidence that centrifuge spinning might negatively impact cognitive functioning. However, due to sample size limitations, it cannot be ascertained whether there were significant differences in cognitive performance between the treatment and control groups. If centrifugation had a negative effect on cognitive functioning, consistent decrements would be expected to be found with all treatment subjects across time. Individual differences in underlying cognitive ability and motivation level are other possible explanations for the results found in this study.

Sipes, Walter E.↗
NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗
NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗
NASA NTRS2022

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Timothy M. Lahmers↗
NASA NTRSDate not supplied

Early And Late Neurobehavioral Effects Of Male And Female Mice Exposed To Five-Ion GCRSim

With upcoming missions to the Moon and beyond to Mars, it is increasingly imperative to elucidate the detrimental effects of space travel beyond the lower Earth orbit, particularly to galactic cosmic radiation. Additionally, with the first female astronaut to soon travel to the Moon there is a strong need to understand the biological sex differences to adaptation to the deep space environment. While the effects of spaceflight on the nervous system are not fully known, studies in animal models have shown that exposure to ionizing radiation can cause neuronal damage and lead to downstream cognitive and behavioral deficits. Here, we investigated the neurobehavioral responses to space environment-like radiation exposure. Male and female 23–24-week-old mice (age-matched to average astronaut age) were exposed to 5, 15 and 50 cGy via Five-Ion Galactic Cosmic Ray Simulation at the NASA National Space Radiation Laboratory at Brookhaven National Laboratory. Both early (72hrs post exposure) and late (1-4 months post exposure) cognitive and behavioral deficits were investigated. Early analysis was performed by observing in-cage behavior including frequency/duration of digging, rearing, and grooming and nestlet building. Additionally, late effects were analyzed at NASA Ames via in-cage behavior as well as Catwalk (gait), Zero Maze (anxiety), Adhesive Removal (sensory motor), Novel Object Recognition and Barnes Maze (working memory). There were pronounced sex differences in both early and late time points. Females scored better than males in nestlet building, gait and working memory while males scored better at the sensory motor (adhesive removal) test. Dose effects were primarily observed at 50 cGy for both sexes, particularly with the Barnes Maze (working memory), where both males and females exposed to 50 cGy showed little to no improvement in test performance, though females again performed better than males. Currently, we are investigating the correlations between the observed behavior and cytokine levels in the plasma and brain. Future studies will continue to investigate cognitive consequences of galactic cosmic radiation in combination with other space-like environment stressors, including antigravity and social versus single housing.

S Puukila↗
NASA NTRS2021

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25 degree) global constituent prediction system from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA’s broad range of space-based and in-situ observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.Evaluation of GEOS-CF against satellite, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 generally overestimates aerosols by 20-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions.The 5-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗
NASA NTRS2020

Deep Space Human-Systems Research Recommendations for Future Human-Automation/Robotic Integration

Appropriate integration between automation and robotics systems and their human operators is essential for future space exploration. The Human Factors and Behavioral Performance Element of NASA’s Human Research Program requires a systematic understanding of the critical human-automation/robotic (HAR) integration, or HARI, design challenges for future space exploration. This document reports the results of a systematic assessment of the spaceflight-relevant HARI technologies and research topics addressing critical gaps in spaceflight-relevant HARI knowledge, and prioritizes research required for successful human performance and HAR integration. We reviewed relevant literature across the past ten years and interviewed ten subject matter experts to investigate the current state of HARI technology, challenges facing development, the state of HARI research across a wide range of fields, and opportunities for advancing the state of the art through directed research. This information was used to identify relevant HARI technologies and research topics, as well as factors to assess relative priority of HARI technologies. We worked with NASA stakeholders to weight the factors relevant to assessing HARI specific technologies. A multi-dimensional trade analysis was performed to objectively score HARI research topics and specific technologies to recommended investment priorities for NASA.

human-automation interaction↗
NASA NTRS2016

Food Fortification Stability Study

NASA has established the goal of traveling beyond low-Earth orbit and extending manned exploration to Mars. The length of proposed Mars missions and the lack of resupply missions increases the importance of nutritional content in the food system, which will need a five year shelf life. The purpose of this research is to assess the stability of vitamin supplementation in traditionally processed spaceflight foods. It is expected that commercially available fortification nutrients will remain stable through a long duration exploration mission at sufficient levels if compatible formulation, processing, and storage temperatures are achieved. Five vitamins (vitamin E, vitamin K, pantothenic acid, folic acid, and thiamin) were blended into a vitamin premix (DSM, Freeport, TX) such that the vitamin concentration per serving equaled 25% of the recommended daily intake after two years of ambient storage. Four freeze-dried foods (Scrambled Eggs, Italian Vegetables, Potatoes Au Gratin, Noodles and Chicken) and four thermostabilized foods (Curry Sauce with Vegetables, Chicken Noodle Soup, Grilled Pork Chop, Rice with Butter) were produced, with and without the vitamin premix, to assess the impact of the added fortification on color and taste and to determine the stability of supplemental vitamins in spaceflight foods. The addition of fortification to spaceflight foods did not greatly alter the organoleptic properties of most products. In most cases, overall acceptability scores remained above 6.0 (minimum acceptable score) following six months and one year of low-temperature storage. Likewise, the color of fortified products appears to be preserved over one year of storage. The only exception was Grilled pork Chop and Chicken Noodle Soup whose individual components appear to degrade rapidly over one year of storage. Finally, most vitamins appear to be stable during long-term storage. The only exception was thiamin, which degraded rapidly during the first year of storage at 35˚C. It was previously believed that the imprecise method of fortification would prove problematic for nutrient quantification; however this was only an issue in stored samples of Grilled Pork Chop, Italian Vegetables and Curry Sauce with Vegetables. Year two data may further reveal the extent to which this is a problem, as well as identify overall quality changes over time.

Sirmons, T.↗