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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

The Variable Detection of Atmospheric Escape around the Young, Hot Neptune AU Mic b

Photoevaporation is a potential explanation for several features within exoplanet demographics. Atmospheric escape observed in young Neptune-sized exoplanets can provide insight into and characterize which mechanisms drive this evolution and at what times they dominate. AU Mic b is one such exoplanet, slightly larger than Neptune (4.19 R ⊕ ). It closely orbits a 23 Myr pre-main-sequence M dwarf with an orbital period of 8.46 days. We obtained two visits of AU Mic b at Lyα with Hubble Space Telescope (HST)/Space Telescope Imaging Spectrograph. One flare within the first HST visit is characterized and removed from our search for a planetary transit. We present a nondetection in our first visit, followed by the detection of escaping neutral hydrogen ahead of the planet in our second visit. The outflow absorbed ∼30% of the star’s Lyα blue wing 2.5 hr before the planet’s white-light transit. We estimate that the highest-velocity escaping material has a column density of 10 13.96 cm −2 and is moving 61.26 km s −1 away from the host star. AU Mic b’s large high-energy irradiation could photoionize its escaping neutral hydrogen in 44 minutes, rendering it temporarily unobservable. Our time-variable Lyα transit ahead of AU Mic b could also be explained by an intermediate stellar wind strength from AU Mic that shapes the escaping material into a leading tail. Future Lyα observations of this system will confirm and characterize the unique variable nature of its Lyα transit, which, combined with modeling, will tune the importance of stellar wind and photoionization.

Exoplanets↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗
NASA NTRSDate not supplied

A Community for Polar Early Career Researchers Engaging With the Interagency Arctic Research Policy Committee

The Interagency Arctic Research Policy Committee (IARPC) is tasked with implementation of the Arctic Research Plan (ARP) by coordinating representatives from federal and state agencies, academic, industry, and Indigenous partners with interests in Arctic research. IARPC is organized into several collaboration teams and discipline-specific communities of practice that interface on the IARPC Collaborations website. The Early Career Community of Practice (ECCoP) is one such community that was established to promote the research of early career researchers (ECR) and increase ECR engagement with the ARP, program managers, collaboration teams, and communities of practice. The ECCoP has grown to develop regular newsletters promoting recent ECR research publications ad sharing training, job, funding, and collaboration opportunities relevant to community members at all life stages that self-identify as ECRs. Within IARPC, the ECCoP continues to promote ECR participation in monthly community of practice meetings and webinars and to report on ECR efforts that contribute to deliverables of the ARP Biennial Implementation Plan. Recent activity of the ECCoP includes developing an annual survey of the ECR cohort on IARPC to follow change in demographics over time and to identify community needs to improve diversity and inclusion in the polar research space and to address gaps in training needs for ECRs.

Katy Smith↗
NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗
NASA NTRS2023

Considering Soil Moisture in Models of Climate Impacts on Child Health in Farming-Centric Countries

Soil moisture reflects the amount of water available to crops in the top layer of soil. As such, considering soil moisture provides important insight into water availability and ultimately crop yields in agricultural settings. In studies of climate change, food security, and health, however, soil moisture is rarely empirically considered despite its connection to crop health and yields. In this project, we aim to advance understanding of climate impacts on food security by incorporating soil moisture into quantitative models of child health. Combining spatially referenced health survey data from the Demographic and Health Surveys for 2005 and 2010 in Senegal and 2007, 2011, and 2014 in Bangladesh, with soil moisture data from the Famine Early Warning System Network Land Data Assimilation System, we explore the linkages between sub-annual and sub-seasonal climate conditions and child malnutrition in two rainfed agriculture dependent countries—Bangladesh and Senegal. Results suggest that soil moisture, measured on very short time scales, may be associated with reductions in anthropometric weight-for-height z-scores, but the relationship is highly dependent upon geographic context.

Child health↗
NASA NTRSDate not supplied

Investigation of Hardware and Instrumentation to Measure Hand Grasp Activity with the Spacesuit Gloves

Introduction: During the 2022 suited injury summit, it was hypothesized that there will be concerns for hand and glove injuries for future exploration space missions, especially given the fact that the “total number of Extravehicular activity (EVA) hours and frequency” for lunar surface missions is expected to vastly increase [1]. It has been reported that the hands experienced the greatest “absolute numbers” of reported injuries and far exceeds other injuries during EVA [1, 2]. It was reported that the most fatiguing part of the surface EVA was the repetitive gripping tasks [3]. It was recommended that a “glove sub-team” be created to look at possible injury mechanism and mitigation strategies. Some of the recommendations that were suggested [1] are as follows: examine hand fatigue, utilize motion capture, examine the duration and frequency of hand movements, and identify frequent hand motions. We started assessing hardware and instrumentation to measure hand grasp activity in the pressurized glove environment. The purpose of this test was to perform a hardware evaluation for motion capture (MoCap) gloves obtained from StretchSense (Auckland, New Zealand). The specific gloves used were the Pro Fidelity and SuperSplay to determine the repeatability, reliability, feasibility, and useability inside of a pressurized gloved environment. Methods: The MoCap gloves were customized (e.g., battery/Bluetooth pack relocated to upper arm) to better suit the pressurized testing environment and protect the subject from unintentional injury (Fig. 1). Fourteen total subjects from different demographics (i.e., gender and pressurized glove experience level) participated in this test series. Testing included one session each of a baseline data collection (NASA Johnson Space Center (JSC) building 21) and a spacesuit glove box (Fig. 2 at JSC building 7 room 2027) data collection (under vacuum down to 4.3 psid), where each session lasted 3-5 hours. Controlled and reproducible tasks to systematically evaluate the repeatability and reliability of the hardware were performed during baseline data collection. Additionally, subjects performed simulated EVA-like tasks in a pressurized gloved environment. For all sessions, MoCap gloves were placed on each of the subjects’ hands and the signal from it, or the raw capacitance (Fig. 3), was analysed. The raw capacitance was used to estimate the open and closed hand states between the testing conditions and allow us to provide an offset caused by the pressurized environment. Results & Discussion: Initial observation with the bare hands (baseline) condition showed that the MoCap gloves appeared to track grasping and releasing of the fingers (opening and closing fist) with both high- and low-speed conditions, while adduction and abduction of the fingers were not relatively tracked. A hardware evaluation was done outside of the glove box to assess the reliability and repeatability of the MoCap glove. In one task, a point force was applied to various locations on the back of the hand. When the point force was applied to the space between the 1st digit and the pointer finger, there was a noticeable distortion to the MoCap data. Another task examining an increasing force from a 10 lb. sandbag applied to the back of the hand while lying flat on a table, showed a constant flat line with only a distortion when the weight was increased or added to the back of the hand. Fig. 3 shows an object relocation task where you can see when each individual finger “opened” and “closed” (changed position) when picking up and setting down the dumbbell. When the fingers were stationary, the signal remained relatively flat compared to the peaks and valleys that can be observed in Fig. 3. This study showed promising results and imperative input into an attempt to discriminate between hand states across various functional tasks and should be evaluated with context to the repeatability and reliability outcomes. Depending on the task done inside of the pressurized glove box environment and outside, the results appear to be affected by many different factors (i.e., drift, pressure, hand size, etc.). Significance: If this hardware proves to be reliable and repeatable in determining the open and closed hand states then this may provide critical insight into assisting in the characterization of the pressurized gloved environment and the effect on crew member exertion level. Ultimately, this tool will provide useful data for quantifying the repetitive nature of EVA training and tasks. Acknowledgments: The authors would like to acknowledge the NASA Mars Campaign Office for providing funding for this research. Lastly, thanks to all the engineers and technicians at NASA JSC who helped with this data collection. References: [1] Reiber, et al. (2022), NASA/TM-20220007605; [2] Scheuring, et al. (2009), Av., Sp., and Envir. Med. 80(2). [3] Scheuring, et al. (2007), NASA/TM–2007–214755.

Rachel L Thompson↗
NASA NTRSDate not supplied

101 Surveys in 28 Days - Evaluating Response Rates to a Demanding Request

We report the results of a survey test conducted in advance of a series of community response tests (CRTs) to evaluate response to noise from NASA’s X-59 aircraft. The CRTs will require a substantial number of observations to generate a dose response curve and the timeframe is limited due to resource and scheduling constraints with an experimental aircraft. Within each CRT area, we will recruit a sample of residents in advance and ask them to fill out a brief survey each time the aircraft passes over. Respondents will be asked to fill out the survey either on the web or as part of an application they are able to download onto their mobile phones. On many days, respondents will be asked to fill out the survey for multiple passes. The survey test followed the proposed methodology of the CRTs, albeit gauging reactions to normal in-situ aircraft events. To demonstrate initial interest, we will present response rates to the recruitment portion of the survey test which used an ABS frame. We will then evaluate the ongoing response rates among the recruited population to a demanding survey schedule involving 101 surveys over a 28-day period. The response rate evaluation will focus on demographics, mode (app vs. web) and whether and how these change over time. We will use the results of this work to confirm or improve the design of the CRTs, ensuring the collection of data needed by NASA to evaluate the impact of this innovative technology.

response rates↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS The following study seeks to inform the risk associated with altered sensorimotor and vestibular function impacting critical mission tasks. We aim to characterize the effects of short and long-duration weightlessness on manual control following G-transitions using simulated lunar landing on a six-degree-of-freedom (6DOF) motion base, a fixed base simulation, and a supervisory control tablet task. The primary goal is to understand the impact of spaceflight on crew ability to perform manual crew override and supervisory control. This aim will be assessed by comparing pre- versus postflight simulation performance in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). We hypothesize there will be postflight increases in the percent time that pilots are outside of the acceptable range for recommended vehicle state parameters and the reaction time for secondary cognitive tasks. Ground-based control subjects, who are demographically matched to the crew considering age (± 5 years) and gender, will undergo the same testing schedule as the crew to examine the effects of flight phase independent of microgravity exposure. The second aim is to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency. Crew performance for a sensorimotor perceptual test battery will evaluate motion perception tracking, roll nulling, and/or vection sensitivity using the 6DOF motion base. We hypothesize that a higher severity of vestibular alterations will be associated with increased percent time outside of guidance limits. Motion sickness severity and sleepiness will also be evaluated. To determine the impact of “just-in-time” training, the third aim seeks to compare performance during on-board lunar landing tasks conducted late in-flight to early postflight. We hypothesize that proficiency on the “just-in-time” laptop trainer late in mission will be positively correlated with early postflight proficiency on the same task. The final aim will establish assessments of performance, training protocols, and the learning progression in a ground-control cohort of first-time users. RESULTS The assessment of the learning progression associated with the piloting task on the motion base system with thirty ground subjects will be reported. Learning curves will be established across four distinct sessions and within session considering trial difficulty. The difficulty of the landing task can be modulated with the landing divert distance and cross or downrange difficulty. Results may include changes in performance across multiple trials of a multi-attribute lunar tablet supervisory control task. Preliminary investigations of eighteen subjects who completed vestibular threshold and motion perception tasks offer expected performance ranges for upcoming preflight crew evaluations. The results yielded an average roll threshold of 0.46 ± 0.30 deg/s and an average roll nulling root mean square error performance of 2.52 ± 0.52 deg/s. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the manual control risks associated with sensorimotor alterations. Ground testing will evaluate learning progression, refine training protocols, and serve as a control cohort for comparisons to crew performance. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, the Dynamic Skills Trainer (DST) Lab, and the Software, Robotics, and Simulation Division toward the development of the lunar landing simulation platforms. This project is funded by the Human Health Countermeasures Element.

Hannah M. Weiss↗
NASA NTRSDate not supplied

Urban Expansion and Climate Change: Investigating the Impact of Future Scenarios on Child Health

Cities in the poorest countries of the world are rapidly urbanizing. In fact, some of the fastest growing cities on the planet are found in sub-Saharan Africa. Many people benefit from economic, educational, and health opportunities that exist in cities and, as a result, city-dwellers often face less risk of poverty and disease in the context of climate change than their rural-dwelling counterparts. However, rapid urbanization, resulting from a large and constant influx of migrants from rural areas, can put pressure on existing social, economic, and health systems. For poor cities, they face a challenge to support existing residents while also expanding to support the needs of migrants, many of whom are deeply impoverished. Additionally, in a climate change, linked to heat waves, floods, droughts, and other related events, can add stress to complex urban food, health, hygiene, and housing systems. In this project we investigate urban expansion, climate change, and health in four major African cities – Ouagadougou, Addis Ababa, Nairobi, and Kigali. We consider different scenarios of urban expansion using historic and contemporary maps of urban extent, combined with climate (temperature, rainfall, and vegetation) and land cover combined with spatially referenced health information from the Demographic and Health Surveys (DHS) to investigate the relationships between urban dwelling, climate change and health. Temperature and rainfall scenarios are developed under different urban land use futures (expanding agricultural areas versus reducing agricultural areas) to examine the ways that individual health outcomes related to malnutrition vary under different potential future conditions. Preliminary results of the research highlight the importance of temperature for health, in particular, and suggest that while urban conditions related to urban infrastructure (e.g., educational attainment, electricity access, and improved hygiene) cannot reduce health risks to counter the impacts of high temperatures and reduced agricultural land. As cities in poor countries urbanize, city-dwellers face unique risks when droughts, heat waves, and other extreme weather events occur. In this project we explore urban land use conditions, climate conditions and health using future scenarios. Specifically we evaluate health outcomes in the future while considering different land use practices, urban expansion, temperature, and rainfall conditions to identify individual-level risk and protective factors. We compare results across four major cities in sub Saharan Africa.

Public Health↗
NASA NTRSDate not supplied

Exploring our Changing Planet through NASA’s Earth Information Center and Novel Methods for Earth Science Communication

In June 2023, NASA unveiled the Earth Information Center (EIC), an interagency initiative which invites the global community to explore how our planet is changing through interactive installations, captivating visualizations, and novel storytelling. Existing in both physical and virtual space, the EIC serves as a gateway to actionable information collected through an expanding fleet of Earth observing satellites and sensors. The EIC features data driven visualizations, near real-time information, immersive experiences, and curated stories that highlight the applications of publicly available data to address environmental challenges across nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, air quality, sea level rise, sustainable energy, water resources, and wildfires. Designed by an interdisciplinary team, EIC exhibits are developed to reach a wide base of end-users across multiple learning modalities. During the first year of operation, the inaugural location of the EIC at NASA Headquarters in Washington, DC, welcomed an estimated 24,000 visitors, hosted over 145 tours for domestic and international organizations, supported NASA’s Earth Day 2024 programming, and led six STEM programs for diverse student communities. With lessons learned from the first year of being open to the public and a variety of novel science communication tools in development, the EIC is expanding the mission’s reach by collaborating with museums and visitor centers. Through these collaborations, we aim to inform a broader demographic about the unprecedented changes observed in Earth’s climate and inspire communities to learn more about their one and only home, planet Earth.

Nicole Ramberg-Pihl↗
NASA NTRSDate not supplied

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗
NASA NTRS2024

Origins of Super Jupiters: TOI-2145b has a Moderately Eccentric and Nearly Aligned Orbit

Super Jupiters are giant planets with several Jupiter masses. It remains an open question whether these planets originate with such high masses or grow through collisions. Previous work demonstrates that warm super Jupiters tend to have more eccentric orbits compared to regular-mass warm Jupiters. This correlation between mass and eccentricity may indicate that planet–planet interactions significantly influence the warm giant planet demographics. Here, we conducted a detailed characterization of a warm super Jupiter, TOI-2145b. This analysis utilized previous observations from Transiting Exoplanet Survey Satellite and Keck/High Resolution Echelle Spectrometer, enhanced by new Rossiter–McLaughlin effect data from the NEID spectrometer on the 3.5 m WIYN Telescope. TOI-2145b is a 5.68 +0.37 −0.34 M Jup MJup planet on a moderate eccentricity (e = 0.214 +0.014 −0.014 ), 10.26 day orbit, orbiting an evolved A-star. We constrain the projected stellar obliquity to be λ = 6.8 +2.9 −3.8 ° from two NEID observations. Our N-body simulations suggest that the formation of super Jupiter TOI-2145b could involve either of two scenarios: a high initial mass or growth via collisions. On a population level, however, the collision scenario can better describe the mass–eccentricity distribution of observed warm Jupiters.

Jiayin Dong↗
NASA NTRS2006

Future Mission Trends and their Implications for the Deep Space Network

This viewgraph presentation discusses the direction of future missions and it's significance to the Deep Space Network. The topics include: 1) The Deep Space Network (DSN); 2) Past Missions Driving DSN Evolution; 3) The Changing Mission Paradigm; 4) Assessing Future Mission Needs; 5) Link Support Trends; 6) Downlink Rate Trends; 7) Uplink Rate Trends; 8) End-to-End Link Difficulty Trends; 9) Summary: Future Mission Trend Drivers; and 10) Conclusion: Implications for the DSN.

mission trends↗
NASA NTRS2012

Deep Space Mission Trend Analyses: A Briefing to the Next Generation EBRE Study Team

Determination of stakeholder needs for next generation implementations necessitates a multi ]pronged approach. . Future mission set analyses provide a lower gbound h for some of these needs. . Earth ]based analogies provide an upper gbound h for some of these needs. . Interpreting the results requires being mindful of both the near ]term contextual factors and long ]term factors that are in play. . In the context of last year fs analyses, the current budget environment, the potential Pu ]238 shortage, and SMD fs gsingle 34m only h policy may, collectively, create a future deep space mission set that, from a capacity and end ]to ]end link difficulty standpoint, is no more challenging than it is today. . Nonetheless, data rates and volumes continue to increase, suggesting capability and spectrum challenges ahead. These results agree with the results from the Earthbased analogies. . Emerging developments such as smallsats and distributed spacecraft could significantly change the capacity and end ]to ]end link difficulty picture.

future mission analysis↗
NASA NTRS2023

Accounting for Herbaceous Communities in Process-Based Models Will Advance Our Understanding of “Grassy” Ecosystems

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

biogeochemistry↗