SEARCH · Engineering Papers

Results for “Comprehension”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS2019

UH-60A Airloads Flight Test Program: Data Counter 9505

The data collection portion of the UH-60A Airloads Flight Test Program (ref. 1) was conducted between July 1993 and February 1994. At the time, the UH-60A Airloads Program was the most comprehensive and data-rich rotorcraft flight test program that NASA and the U.S. Army had ever attempted. It was part of the Modern Technology Rotors Program (ref. 2), where several different rotors were tested in small- and full-scale wind tunnels combined with flight testing. The UH-60A portion of this program allowed for comparison between other tests performed and served as a scientific quality database for validating current and new computational and simulation models. The UH-60A flight test data was stored in a comprehensive, easily accessed database known as the Tilt Rotor Engineering Database System, or TRENDS (ref. 3). With over 30 years of rotor testing experience (ref. 4), NASA and the Army’s goal of the Airloads Flight Test Program was to collect data for a wide range of operating conditions, and to provide an extensive amount of data to improve the understanding of rotors and validate and improve prediction codes. This report presents the entire archived data set from Counter 9505 (Run 95, point 5) from the UH-60A Airloads Flight Test Program. There were 1,078 total data set counters acquired and archived during 57 accumulated flight hours and 31 research flights. Over 900 counters were research flight data acquisition data points. Counter 9505 is a low altitude, moderate airspeed, level-flight test condition. Ground acoustic microphone data was acquired for this counter but the acoustic data is not included in this report.

Kufeld, Robert M.↗

NASA NTRS2020

Modeling Electrolytic Conversion of Metabolic CO2 and Optimizing a Macrofluidic Electrochemical Reactor for Advanced Closed Loop Life Support Systems

The International Space Station (ISS) is currently equipped with a complex, heavy, and power consuming system that recovers approximately 50% of O2 from metabolic CO2. Future long duration missions will require a sustainable and highly efficient system capable of yielding a minimum of 75% O2 recovery. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to significantly increase current O2 recovery efficiency and reduce complexity of the system. This paper presents a comprehensive multi-physic 3D model developed at MSFC on CO2 conversion to O2 and C2H4 at standard conditions via MFECR. The 3D spatial domain of the model is a replica of the actual MFECR’s 3D drawing generated for the MFECR fabrication and operated to recover O2 from CO2 yielding C2H4 as byproduct. Electrochemical (EC) physics that includes EC multicomponent reaction mechanisms, mass transport, and current density distributions is coupled in the model with all the other physics phenomena involved in the process, such as free and porous fluid flow, multicomponent mass transfer, heat transfer, and DC electrical current generation along with Joule heating effect. The authors plan to use experimental results to validate this comprehensive and rigorous model and build a reliable simulator that will not only assist the authors on the MFECR design but also optimize its operation.

Dominguez, Jesus A.↗

NASA NTRS2020

Spectral Evidence for Heating at Large Column Mass in Umbral Solar Flare Kernels. I. IRIS Near-UV Spectra of the X1 Solar Flare of 2014 October 25

The GOES X1 flare SOL2014-10-25T17:08:00 was a three-ribbon solar flare observed with the Interface Region Imaging Spectrograph (IRIS)in the near-UV(NUV)and far-UV. One of the flare ribbons crossed a sunspot umbra, producing a dramatic, ∼1000% increase in the NUV continuum radiation. We comprehensively analyze the UV spectral data of the umbral flare brightenings, which provide new challenges for radiative−hydrodynamic modeling of the chromospheric velocity field and the white-light continuum radiation. The emission line profiles in the umbral flare brightenings exhibit redshifts and profile asymmetries, but these are significantly smaller than in another, well-studied X-class solar flare. We present a ratio of the NUV continuum intensity to the FeIIλ2814.45intensity. This continuum-to-line ratio is a new spectral diagnostic of significant heating at high column mass (log m/[gcm−2]>−2) during solar flares because the continuum and emission line radiation originate from relatively similar temperatures but moderately different optical depths. The full spectral readout of these IRIS data also allow for a comprehensive survey of the flaring NUV landscape: in addition to many lines of Fe II and Cr II, we identify a new solar flare emission line, HeIλ2829.91(as previously identified in laboratory and early-type stellar spectra). The Fermi/GBM hard X-ray data provide inputs to radiative−hydrodynamic models (which will be presented in Paper II) in order to better understand the large continuum-to-line ratios, the origin of the white-light continuum radiation, and the role of electron beam heating in the low atmosphere.

Adam F Kowalski↗

NASA NTRSDate not supplied

Preliminary Design of an 'Autonomous Medical Response Agent' Interface Prototype for Long Duration Spaceflight

Major challenges for astronauts in future long-duration exploration missions (LDEMs) will be that crewmembers are not expected to be medical professionals, may be under high workload and stress, are facing physiological challenges caused by spaceflight, and will have limited, delayed voice communications with medical support from Earth. An autonomous medical response agent (AMRA) is envisioned to help astronauts address medical complaints, develop a differential diagnosis, and guide self-treatment until a healthy state is restored. AMRA develops a process of personalized diagnosis and treatment through a Bayesian predictive control system that recommends therapeutic control actions including diagnostic tests and treatments to crewmembers (Menon, 2020). The Human Computer Interaction (HCI) lab from NASA Ames Research Center’s Human Systems Integration Division (Code TH) has collaborated with Nahlia Inc in human-centered design augmentation research for AMRA. The project, titled Design of ‘Autonomous Medical Response Agent Interface Prototype for Long Duration Spaceflight, has been funded by the Translational Research Institute for Space Health (TRISH) and introduces an interactive user-interface prototype that guides astronauts through self-diagnosis, treatment, and rehabilitation while communicating with remote specialists in ground support (most notably a patient’s flight surgeon). Our project develops the interaction design for the crewmember using AMRA through user research, iterative design, and usability testing to evaluate the user interface and workflow designed. The interface design deliverable for this project, titled AMRA Aggregate Information Display (AMRA AID) is an integrated information display system for comprehensive autonomous medical guidance, diagnosis, and treatment of in-flight medical conditions experienced by crewmembers. AMRA AID demonstrates how we might ensure crew autonomy, increase the crew’s medical capabilities, and decrease cognitive burden within a front-end user interface. AMRA AID refrains from relying on input from ground or mission control for self-treatment of medical issues—though ground awareness and communication with ground is maintained as a means of ensuring trust between mission control and crew. AMRA AID demonstrates how the crew’s on-board medical system might integrate with information from vehicle monitoring and crew schedule, without assuming causal relationships. AMRA AID’s comprehensive view enables efficient information access for both crew and ground support, reducing cognitive burden in the event of an unplanned or emergency medical incident and enabling informed analytical decisions to be made based on both crew and vehicle health. Human-centered design augmentation advanced within the prototype included: enhanced workflow and treatment guidance for two medical scenarios for a non-specialist user base with various levels of medical training, interaction design which considered speech (conversational user interface) elements and on-screen interactions to be developed in future iterations of the project, communication design and functional requirements relevant to self-care versus caring for another astronaut, as well as user testing of the prototype with an international space medical community. This project arrives at critical findings regarding usability needs, communication requirements, and integrated information requirements for a future technology interface functioning to increase confidence between ground support and LDEM crewmembers.

TRISH↗

NASA NTRSDate not supplied

TriTruss Packaging and Deployment Trade Study

An architecture and feasibility study of next generation In-Space Assembled Telescopes (iSAT) concluded that robotic in-space assembly of modular components is necessary to enable large (>15-meter diameter) primary apertures. The iSAT study recommended that the foundational structure be assembled from modular TriTruss modules that are packaged for launch, deployed on-orbit and robotically assembled into the final configuration. This paper will describe and summarize the results of a trade study that investigated viable concept of operations (ConOps) for the packaging and deployment (P&D) of individual planar TriTruss modules that could be assembled to form a large aperture iSAT. The ideal TriTruss P&D concept is defined as one that: allows for efficient packaging; has sufficient geometric versatility to be launch vehicle independent; provides a stiff and lightweight structure; has low mechanical complexity; and has component modularity. The P&D concept should allow for prelaunch subsystem or utility integration if required. The concept would be kinematically simple and be robotically deployed using a minimum number of specialized tools. In this first phase of an ongoing more comprehensive trade study, concepts were proposed and then evaluated based on initial metrics representing features of an ideal P&D concept. The P&D concepts evaluated are categorized as: core collapse, face collapse, and erectable structures. Sub-scale models were constructed to help understand the kinematics and mechanical complexity required to enable P&D. Based on a weighting scale, the most promising candidate P&D concepts have selected and will undergo more rigorous structural design, analysis, and testing in the study’s next phase. The ultimate goal of the comprehensive trade study will be to recommend a single TriTruss design and associated P&D concept that will be built and evaluated at NASA Langley Research Center’s In-Space Assembly Laboratory.

in-space assembly (ISA)↗

NASA NTRSDate not supplied

TriTruss Packaging and Deployment Trade Study

A trade study was conducted that evaluated viable concepts of operation for the packaging and deployment (P&D) of novel deployable modular truss modules, called TriTruss modules, that can be assembled to form a large aperture In-Space Assembled Telescopes (iSAT). In this first phase of an ongoing more comprehensive trade study, concepts were proposed and then evaluated based on initial metrics representing features of an ideal P&D concept. The ideal TriTruss P&D concept is defined as one that: allows for efficient packaging, has sufficient geometric versatility to be launch vehicle independent, provides a stiff and lightweight structure, has low mechanical complexity, and has component modularity. The P&D concept should allow for prelaunch subsystem or utility integration if required. The concept should be kinematically simple and be robotically deployed using a minimum number of specialized tools. The P&D concepts evaluated are categorized as: core collapse, face collapse, and erectable structures. Sub-scale models were constructed to help understand the kinematics and mechanical complexity required to enable P&D. Based on a weighting scale, the most promising candidate P&D concepts have been selected and will undergo more rigorous structural design, analysis, and testing in the study’s next phase. The ultimate goal of the comprehensive trade study will be to recommend a single TriTruss design and associated P&D concept that will be built and evaluated at NASA Langley Research Center’s In-Space Assembly Laboratory.

in-space assembly (ISA)↗

NASA NTRSDate not supplied

Model-Based Systems Engineering, Real-Time Operations, and Autonomy

Model-Based Systems Engineering has been enabled by the development of the SysML language and software tools to create systems models. Systems models described in SysML incorporate frames (Diagrams) that represent behaviors (activities, sequences, state machines, use cases), requirements, and structure (definitions, internal structure, parametric formulation, and packaging). The SysML models are, in turn, used by applications to do analysis and studies of the designs and operational capabilities. These uses of the model are based on simulations, and do not include hardware. This paper presents a software environment and processes that enables more comprehensive systems models for MBSE, and use of these rich models for real-time operations. The paper describes a software platform that enables creation of comprehensive models, beyond what is now possible with SysML and related software tools, called the NASA Platform for Autonomous Systems (NPAS). The platform encapsulates a paradigm and infrastructure for creating systems models with complexity levels comparable to the ones handled by SysML software tools, but with additional fidelity that includes detailed design diagrams encompassing sensors, components, and design topologies. Furthermore, NPAS enables incorporation of data, information, and knowledge (DIaK) to implement autonomy and Integrated System Health Management (ISHM) and the inherent integration of content encompassing SysML structure and behavior diagrams throughout the NPAS modelAnd lastly, the NPAS models are used in real-time operations, taking advantage of the fidelity and complexity encompassed in the models in order to implement “thinking” ISHM and/or autonomous operations. . Incorporation of SysML model content into an NPAS model is briefly discussed.

MBSE↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

clinical decision support↗

NASA NTRS2021

Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios

Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.

crop yield projections↗

NASA NTRS2021

Exploration Mission Tasks: A Technical Manual

This technical manual is an abridgement of the Generalizable Skills and Knowledge for Exploration Missions (NASA/CR-2018-22045) report (Stuster et al., 2019), describing research conducted under Cooperative Agreement 80NSSC18K0042 for the Human Factors and Behavioral Performance Element, Human Research Program, located at the National Aeronautics and Space Administration’s (NASA) Johnson Space Center. The research identified tasks that will be conducted by human crew during an expedition to Mars, and the abilities, skills, and knowledge that will be required of crew members. The 3-year study uses research methods that were developed to analyze the work performed by a variety of civilian and military occupational specialties and is consistent with Human Factors methods. The work began by developing a comprehensive inventory of 1,125 tasks that are likely to be performed during the 12 phases of the first human expeditions to Mars, from launch to landing 30 months later. Sixty subject matter experts (SMEs) rated expedition tasks in terms of (likely) frequency of performance, difficulty to learn, and importance to mission success; a fourth metric (criticality), was derived by summing the mean ratings of the three dimensions. Seventy-two SMEs placed the physical, cognitive, and social abilities necessary to perform the tasks in order of importance for specialist domains identified by the task analysis. The research team then identified: 1) Abilities, skills, and knowledge that can be retained and generalized across tasks and 2) Implications for crew size and composition. Study results also led to recommendations concerning equipment, habitats, and procedures for exploration-class space missions. Note: The full-mission task inventory was developed during a comprehensive review of documentation and concepts of operations. It was understood by the study team that the tasks were based on currently available information, and that the tools, equipment, propulsion methods, and/or other aspects of actual human expeditions to Mars might be different from those described here, as a consequence of technological development and evolving Mars Design Reference Missions. The purpose and scope of this technical manual is to present the core, actionable information that resulted from this research. The abridged format is intended to address the needs of development and research teams to quickly access, discern, and use the information in the course of their exploration-related work.

Brandin Munson↗

NASA NTRSDate not supplied

The Atmosphere Observing System (AOS): Synergistic Aerosol, Cloud, Convection and Precipitation Measurement and Modeling Systems

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (ACCP), with the ACCP Study concluding in early 2021. The new mission now in pre-phase A is being referred to as the Atmosphere Observing System (AOS), an integral part of NASA’s Earth System Observatory (ESO) strategy. The DS and the ACCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those of the individual DOs. A critical element of the ACCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. In order to achieve maximum benefit, all these observations need to be integrated into comprehensive observing and modeling/data assimilation systems. Such an approach requires comprehensive model-data synthesis capabilities that needs to be conceived in conjunction with the space-based and suborbital components of AOS. In this presentation we will summarize the major science goals of AOS including cloud feedbacks, atmospheric convection, emphasizing aerosol processes and aerosol radiative effects, and the synergistic aspects of clouds-precipitation-aerosol interactions. We will describe examples of how AOS data will be used across space and time to better initialize forecasts and train modeling systems, and to infuse models and data assimilation systems with AOS data for advancing operational predictions and to generate expanded hindcasts and reconstruction of the climate record.

Arlindo da Silva↗

NASA NTRS2022

Haiti Agriculture: Utilizing NASA Earth Observations to Evaluate the Success of Reforestation Practices in Haiti

Haiti is one of the world’s most deforested and environmentally degraded countries. Over the past 30 years, the Haiti Reforestation Partnership (HRP) has provided resources, education, and expertise to support reforestation work in Haiti. The HRP has planted over 15 million trees through their partnership with Comprehensive Development Program (CODEP). However, they have yet to conduct a comprehensive analysis of forest stand survival. The NASA DEVELOP team partnered with the HRP to aid their future silvicultural decisions using satellite imagery. Through the creation of the Monitoring of Vegetation Presence (MVP) tool in Google Earth Engine, the team produced a time series showing trends in enhanced vegetation index (EVI) from 1984 to 2021, as well as a habitat suitability map using a general model for all tree species. These provided the partner with visuals to communicate their reforestation efforts and guidance on where to apply their future efforts. The team utilized Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2 and Sentinel-2 Multispectral Instrument (MSI) vegetation indices as indicators of stand success over time. The team also incorporated WorldClim bioclimatic variables such as precipitation and temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar elevation, and ancillary datasets areas suitable for future reforestation efforts. Overall, the time series showed that the demonstration forest increased in EVI at a greater rate than the surrounding area and the habitat model suggested there are 49,000 hectares of suitable habitat for planting using slope, aspect and temperature as predictor variables.

Kelli Roberts↗

NASA NTRSDate not supplied

Computational Analysis of a Quiet Single-Main Rotor Helicopter for Air Taxi Operations

A computational study has been done on NASA’s quiet single-main rotor helicopter concept for urban air mobility using high-fidelity computational fluid dynamics, rotorcraft comprehensive analysis tools, and computational aeroacoustics. High-order accurate schemes, dual-time stepping, and the delayed detached-eddy simulation model have been employed. A loose-coupling approach between the flow solver and the rotorcraft comprehensive code is implemented to include vehicle trim and blade motions. Acoustic simulations based on the Ffowcs-Williams and Hawkings equations have been performed to compute the rotor noise. Different blade geometries and tip speeds are analyzed, and performance and acoustics results are compared. The vehicle has been simulated in hover and cruise, with flight conditions representative of an air taxi mission. The quiet single-main rotor helicopter is one of the conceptual designs intended to focus and guide NASA’s research activities in support of aircraft development for vertical take-off and landing air taxi operations.

ARMD↗

NASA NTRSDate not supplied

Reanalysis of Rodent Data from Spacelab Life Sciences-1

The space bioscience field has long been plagued by the challenge of spaceflight with effects of radiation and microgravity. Having multiple and repeated spaceflight experiments for model organisms to solve these space stressors is costly and time consuming. Therefore, reusing and reanalyzing legacy experiments is one way that scientists can draw new conclusions in a timely manner and without using too many resources. Moreover, advances in general biological knowledge allows legacy experiments to be placed into more complete context.Here we aim to analyze all data and metadata taken from rats flown on the SLS-1 mission to create a comprehensive biological model that can be supplemented with current data to allow new discoveries in how space flown organisms adapt to the space environment. Our approach begins with the identification of all the data and metadata, including graphs and tables, for SLS-1 in NASA archives and other sources. Then, each piece of data and metadata will be digitized, reformatted and analyzed. Lastly, a previously developed astronaut model will be used to create the data framework and a comprehensive biological rodent model. The datasets we are using is from the 1991 SpaceLab Life Science 1 (SLS-1) NASA Mission. This was the first designated spacelab mission flown. All 29 rodents were tested for nine days in two different habitats: Research Animal Holding Facility (RAHF) and Animal Enclosure Module (AEM). The rodents were prepared for a live return and compared to a ground control. A total of 30 rodent experiments were accepted as flight studies on the mission. By digitization and reorganizing SLS-1 rat data we will both directly generate new insights and indirectly enable other scientists to by providing the data and metadata in a digitized form.

Space Biology↗

NASA NTRSDate not supplied

Landslide Susceptibility and Runout Assessment for the Arun Hydropower Cascade in Nepal Based on Multitemporal Landslide Inventory Developed Using Planet Imagery

The transboundary Pumqu/Arun River basin spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows forming the Arun River once it enters Nepal. The Arun River valley has about 3,163 MW in five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the Arun River valley must be identified. We generated a multitemporal landslide inventory (2010-2020), modeled landslide susceptibility and runouts around the hydropower sites using Earth Observation (EO) techniques. We used high-resolution satellite imagery from Planet and open-source tool to establish a detailed and comprehensive multitemporal landslide inventory for the basin. The rigorous quality-controlled inventory represents yearly record of landslides from 2010 to 2020. To our knowledge this is one of the most comprehensive landslide inventories for the basin with yearly records of landslides.A data-driven approach was used to map areas susceptible to landslides within the Pumqu/Arun River basin. The multitemporal landslide inventory combined with other readily available EO-based variables were used to create a landslide susceptibility map. The highly susceptible areas delineated from the map was further used to characterize runouts near the hydropower sites. The susceptibility and runout analysis provide a valuable initial estimate of where landslides are likely to trigger and where the mobilized material is likely to end up.

Pukar Amatya↗

NASA NTRS2022

Imaging the End-to-End Dynamics of the Global Solar Wind-Magnetosphere Interaction

Much of what we know about the solar wind’s interaction with the Earth’s magnetosphere has been gained from isolated in situ measurements by single or multiple spacecraft. Based on their observations, we know that reconnection, whether on the dayside magnetopause or deep within the Earth’s magnetotail, controls the flow of solar wind energy into and through the global system. We know that nightside activity provides the energized particles that power geomagnetic storms. But by their very nature these isolated in situ measurements cannot provide an instantaneous global view of the entire system or its cross-scale dynamics. As a result, we don’t know which mode of reconnection prevails on the dayside magnetopause or within the magnetotail as a function of solar wind and geomagnetic conditions. We don’t know which mode or modes of nightside activity supply the most energized particles to the ring current. Nor do we know the dominant loss mode for ring current decay: precipitation, magnetopause outflow, or charge exchange with neutrals. Nor do we know how processes deep within the magnetosphere provide feedback to those happening in the outer magnetosphere. The answers to these questions could have an impact far beyond magnetospheric physics, since magnetic reconnection, particle acceleration, and charge-exchange are fundamental plasma processes that operate at other planets and throughout the universe. Comprehensive end-to-end global imaging of the key micro, meso-, and macro-scale plasma structures that comprise the magnetosphere will provide the answers to these questions via observations with a spatial resolution that exceeds anything possible with in situ measurements. Each proposed interaction mechanism generates a diagnostic plasma structure or boundary signature. Global, end-to-end, imaging provides the pathway to understanding the system as a whole, its constituent parts, and its cross-scale processes on a continuous basis, as needed to quantify the flow of solar wind energy through the global magnetospheric system. The significance of each mechanism is the product of its amplitude and occurrence rate. This white paper describes how a comprehensively-instrumented single spacecraft in a high-latitude circular polar orbit can provide the essential observations needed to track and quantify the flow of solar wind energy through the magnetosphere, including the solar wind plasma and magnetic field input, the magnetopause location in soft X-rays, the auroral oval in far ultraviolet, the ring current in energetic neutrals, the plasmasphere in extreme ultraviolet, the exosphere in Lyman-, the microstructure of the nightside auroral oval in ground-based all sky cameras, and the magnetic perturbations of ionospheric current patterns seen by ground-based magnetometers.

D G Sibeck↗

NASA NTRS2022

Exploring the Relationship Between Temperature Forecast Errors and Earth System Variables

Accurate subseasonal weather forecasts, from two weeks up to a season, can help reduce costs and impacts related to weather and corresponding extremes. The quality of weather forecasts has improved considerably in recent decades as models represent more details of physical processes, and they benefit from assimilating comprehensive Earth observation data as well as increasing computing power. However, with ever–growing model complexity, it becomes increasingly difficult to pinpoint weaknesses in the forecast models’ process representations which is key to improving forecast accuracy. In this study, we use a comprehensive set of observation–based ecological, hydrological and meteorological variables to study their potential for explaining temperature forecast errors at the weekly time scale. For this purpose, we compute Spearman correlations between each considered variable and the forecast error obtained from the ECMWF subseasonal–to–seasonal (S2S) reforecasts at lead times of 1–6 weeks. This is done across the globe for the time period 2001–2017. The results show that temperature forecast errors globally are most strongly related with climate–related variables such as surface solar radiation and precipitation, which highlights the model’s difficulties in accurately capturing the evolution of the climate–related variables during the forecasting period. At the same time, we find particular regions in which other variables are more strongly related to forecast errors. For instance, in central Europe, eastern North America and southeastern Asia, vegetation greenness and soil moisture are relevant, while in western South America and central North America, circulation–related variables such as surface pressure relate more strongly with forecast errors. Overall, the identified relationships between forecast errors and independent Earth observations reveal promising variables on which future forecasting system development could focus by specifically considering related process representations and data assimilation.

Temperature↗