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NASA Education Activities on the International Space Station: A National Laboratory for Inspiring, Engaging, Educating and Employing the Next Generation

The International Space Station (ISS) National Lab Education Project has been created as a part of the ISS National Lab effort mandated by the U.S. Congress The project seeks to expand ISS education of activities so that they reach a larger number of students with clear educational metrics of accomplishments. This paper provides an overview of several recent ISS educational payloads and activities. The expected outcomes of the project, consistent with those of the NASA Office of Education, are also described. NASA performs numerous education activities as part of its ISS program. These cover the gamut from formal to informal educational opportunities in grades Kindergarten to grade 12, Higher Education (undergraduate and graduate University) and informal educational venues (museums, science centers, exhibits). Projects within the portfolio consist of experiments performed onboard the ISS using onboard resources which require no upmass, payloads flown to ISS or integrated into ISS cargo vehicles, and ground based activities that follow or complement onboard activities. Examples include ground based control group experiments, flight or experiment following lesson plans, ground based activities involving direct interaction with ISS or ground based activities considering ISS resources in their solution set. These projects range from totally NASA funded to projects which partner with external entities. These external agencies can be: other federal, state or local government agencies, commercial entities, universities, professional organizations or non-profit organizations. This paper will describe the recent ISS education activities and discuss the approach, outcomes and metrics associated with the projects.

Severance, Mark T.↗

Conclusion

This compilation of papers in this book represents approximately half of the works discussed at the MS&T 2010 symposium entitled Tools, Models, Databases, and Simulation Tools Developed and Needed to Realize the Vision of Integrated Computational Materials Engineering at Materials Science & Technology wherein five sessions comprised of 33 presentations was organized. The goal of the symposium was two fold To provide a forum in which current state-of-the-art methods for ICME (e.g., information informatics, experimentation, and modeling) could be openly discussed and critiqued by not only materials scientist but also structural engineers/researchers, component designers, industrial leaders and government program managers. To leave the symposium and in particular the panel discussion with a clear idea of the gaps and barriers (both technical, cultural and economical) that must be addressed in order for ICME to fully succeed. The organizers felt that these goals were met, as particularly evident by the standing room only attendance during a lively panel discussion session at the end of the Symposium. However it is the firm belief of the editors of this book that this symposium was merely a start in the right direction, and that subsequent conferences/symposium (e.g., First World Congress on Integrated Computational Materials Engineering to be held July 10-14, 2011 at Seven Springs Mountain Resort in Pennsylvania) must work hard to ensure that a truly diverse, multidisciplinary, community of researchers and practitioners are present and have ample opportunity for interaction. This will ensure that a proper balance between push and pull disciplines and technologies is maintained so that this emerging focus area, Integrated Computational Materials Engineering (ICME), has the greatest potential for success and impact on "system-level" payoffs. Similarly, a pro-active approach is required to reform historical modes of operation in industry, government and the academic sectors so as to facilitate multidisciplinary collaboration and to clearly articulate the vision and scope of ICME.

Arnold, Steven M.↗

Development of a Venus Surface Wind Sensor Based on a Miniature Drag-Force Anemometer

To better understand the atmospheric structure and dynamics on the Venus surface and provide input to climate models, there is a need to measure the wind velocity and direction on the surface and track changes over extended periods. A wind sensor based on a miniature drag-force anemometer is being developed to meet the challenges for wind measurements and operational requirements on the surface of Venus. The sensor materials are chosen to enhance durability and prevent reactivity with the Venus surface atmosphere. Advantages of this approach include that it is independent on variable heat transfer, has been matured in other harsh environment applications,and has a low mass and power requirement. This report describes demonstration of this miniature drag-force anemometer integrated with high temperature electronics in simulated Venus surface environment. Prototype drag-force anemometers were demonstrated integrated with an operational amplifier recording transient effects in a simulated Venus surface environment. For multidirectional wind monitoring, the sensors are small enough to be deployed orthogonally as a three-dimensional array on a small arm or mast

wind measurement↗

NASA Tech Briefs, September 2013

Topics include: ISS Ammonia Leak Detection Through X-Ray Fluorescence; A System for Measuring the Sway of the Vehicle Assembly Building; Fast, High-Precision Readout Circuit for Detector Arrays; Victim Simulator for Victim Detection Radar; Hydrometeor Size Distribution Measurements by Imaging the Attenuation of a Laser Spot; Quasi-Linear Circuit; High-Speed, High-Resolution Time-to-Digital Conversion; Li-Ion Battery and Supercapacitor Hybrid Design for Long Extravehicular Activities; Ultrasonic Low-Friction Containment Plate for Thermal and Ultrasonic Stir Weld Processes; High-Powered, Ultrasonically Assisted Thermal Stir Welding; Next-Generation MKIII Lightweight HUT/Hatch Assembly; Centrifugal Sieve for Gravity-Level-Independent Size; Segregation of Granular Materials; Ion Exchange Technology Development in Support of the Urine Processor Assembly; Nickel-Graphite Composite Compliant Interface and/or Hot Shoe Material; UltraSail CubeSat Solar Sail Flight Experiment; Mechanism for Deploying a Long, Thin-Film Antenna From a Rover; Counterflow Regolith Heat Exchanger; Acquisition and Retaining Granular Samples via a Rotating Coring Bit; Very-Low-Cost, Rugged Vacuum System; Medicine Delivery Device With Integrated Sterilization and Detection; FRET-Aptamer Assays for Bone Marker Assessment, C-Telopeptide, Creatinine, and Vitamin D; Multimode Directional Coupler for Utilization of Harmonic Frequencies from TWTAs; Dual-Polarization, Multi-Frequency Antenna Array for use with Hurricane Imaging Radiometer; Complementary Barrier Infrared Detector (CBIRD) Contact Methods; Autonomous Control of Space Nuclear Reactors; High-Power, High-Speed Electro-Optic Pockels Cell Modulator; Covariance Analysis Tool (G-CAT) for Computing Ascent, Descent, and Landing Errors; Enigma Version 12; Micrometeoroid and Orbital Debris (MMOD) Shield Ballistic Limit Analysis Program; Spitzer Telemetry Processing System; Planetary Protection Bioburden Analysis Program; Wing Leading Edge RCC Rapid Response Damage Prediction Tool (IMPACT2); ISSM: Ice Sheet System Model; Automated Loads Analysis System (ATLAS); Integrated Main Propulsion System Performance Reconstruction Process/Models. Phoenix Telemetry Processor; Contact Graph Routing Enhancements Developed in ION for DTN; GFEChutes Lo-Fi; Advanced Strategic and Tactical Relay Request Management for the Mars Relay Operations Service; Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data; Ionospheric Specifications for SAR Interferometry (ISSI); Implementation of a Wavefront-Sensing Algorithm; Sally Ride EarthKAM - Automated Image Geo-Referencing Using Google Earth Web Plug-In; Trade Space Specification Tool (TSST) for Rapid Mission Architecture (Version 1.2); Acoustic Emission Analysis Applet (AEAA) Software; Memory-Efficient Onboard Rock Segmentation; Advanced Multimission Operations System (ATMO); Robot Sequencing and Visualization Program (RSVP); Automating Hyperspectral Data for Rapid Response in Volcanic Emergencies; Raster-Based Approach to Solar Pressure Modeling; Space Images for NASA JPL Android Version; Kinect Engineering with Learning (KEWL); Spacecraft 3D Augmented Reality Mobile App; MPST Software: grl_pef_check; Real-Time Multimission Event Notification System for Mars Relay; SIM_EXPLORE: Software for Directed Exploration of Complex Systems; Mobile Timekeeping Application Built on Reverse-Engineered JPL Infrastructure; Advanced Query and Data Mining Capabilities for MaROS; Jettison Engineering Trajectory Tool; MPST Software: grl_suppdoc; PredGuid+A: Orion Entry Guidance Modified for Aerocapture; Planning Coverage Campaigns for Mission Design and Analysis: CLASP for DESDynl; and Space Place Prime.

Source record↗

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

Frisch, Harold P.↗

Spitzer Space Telescope Sequencing Operations Software, Strategies, and Lessons Learned

The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.

missions operations↗

The Importance of Earth as a Meteor Detector

In order to understand the complex meteoroid environment that threatens spacecraft in near Earth space, ground based observational techniques provide us with an effective option for evaluating the important parameters of flux, speed, mass, density and directionality. While no observational method (in ]situ or ground based detectors) provides bias free measurements of direct quantities, there are several benefits to using the Earth as a detector for calibrating meteoroid models that extend to the inner Solar System and beyond Earth fs orbit. The Earth constantly interacts with meteoritic particles from comets and asteroids as they evolve from their parent objects through dynamical processes. Modeling these dynamical processes with a physics ]based approach can help reveal the causes of observational features but developing those models involves constraining sequences of poorly defined parameters. These parameters must be tuned to a particular detector that offers direct or indirect measurements of mass, density, flux and speed - the quantities used in evaluating penetration risk. The following topics will be discussed: a) Consistency between ground based and in.situ measurements of flux in Earth orbit. b) Consistency between radar and electro.optical speed determinations and agreement of these with dynamical studies. c) The fact that there are six sporadic sources which cannot be determined by integrated line of sight emissivity: Observations using IRAS or COBE cannot give you all important directionality needed for risk evaluations. d) The large collecting area of the Earth s atmosphere compared to in.situ detectors gives better number statistics in the threat regime. The NASA Meteoroid Environment Office utilizes ground based radar and electro.optical measurements to calibrate the Meteoroid Engineering Model (MEM). As MEM is an engineering design model our main emphasis is on threat size particle, speed, flux and directionality. However, MEM has acknowledged limitations particularly with regard to source strength as a function of mass and work is proceeding with improved distributions that will rectify many of these shortcomings.

Koehler, Heather↗

On Automating Failure Mode Analysis and Enforcing its Integrity

This paper reports our experience on the development of a design-for-safety (DFS) workbench called Risk Assessment and Management Environment (RAME) for microelectronic avionics systems. Our objective is to transform DFS practice from an ad-hoc, inefficient, error-prone approach to a stringent engineering process such that DFS can keep up with the rapidly growing complexity of avionics systems. In particular, RAME is built upon an information infrastructure that comprises a fault model, a knowledge base, and a failure reporting/tracking system. This infrastructure permits systematic learning from prior projects and enables the automation of failure modes, effects and criticality analysis (FMECA). Among other unique features, the most important advantage of RAME is its capability of directly accepting design source code in hardware description languages (HDLs) for automated failure mode analysis, which enables RAME to be compatible and to evolve with most electronic-computer-aided-design systems. Through an initial experimental evaluation of the RAME prototype, we show that our approach to FMECA automation improves failure mode analysis turn-around-time, completeness, and accuracy.

design for safety↗

Numerical simulation of rarefied gas flow through a slit

Two different approaches, the finite-difference method coupled with the discrete-ordinate method (FDDO), and the direct-simulation Monte Carlo (DSMC) method, are used in the analysis of the flow of a rarefied gas from one reservoir to another through a two-dimensional slit. The cases considered are for hard vacuum downstream pressure, finite pressure ratios, and isobaric pressure with thermal diffusion, which are not well established in spite of the simplicity of the flow field. In the FDDO analysis, by employing the discrete-ordinate method, the Boltzmann equation simplified by a model collision integral is transformed to a set of partial differential equations which are continuous in physical space but are point functions in molecular velocity space. The set of partial differential equations are solved by means of a finite-difference approximation. In the DSMC analysis, three kinds of collision sampling techniques, the time counter (TC) method, the null collision (NC) method, and the no time counter (NTC) method, are used.

Keith, Theo G., Jr.↗

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

Integrating planning and reactive control

Artificial intelligence research on planning is concerned with designing control systems that choose actions by manipulating explicit descriptions of the world state, the goal to be achieved, and the effects of elementary operations available to the system. Because planning shifts much of the burden of reasoning to the machine, it holds great appeal as a high-level programming method. Experience shows, however, that it cannot be used indiscriminately because even moderately rich languages for describing goals, states, and the elementary operators lead to computational inefficiencies that render the approach unsuitable for realistic applications. This inadequacy has spawned a recent wave of research on reactive control or situated activity in which control systems are modeled as reacting directly to the current situation rather than as reasoning about the future effects of alternative action sequences. While this research has confronted the issue of run-time tractability head on, in many cases it has done so by sacrificing the advantages of declarative planning techniques. Ways in which the two approaches can be unified are discussed. The authors begin by modeling reactive control systems as state machines that map a stream of sensory inputs to a stream of control outputs. These machines can be decomposed into two continuously active subsystems: the planner and the execution module. The planner computes a plan, which can be seen as a set of bits that control the behavior of the execution module. An important element of this work is the formulation of a precise semantic interpretation for the inputs and outputs of the planning system. They show that the distinction between planned and reactive behavior is largely in the eye of the beholder: systems that seem to compute explicit plans can be redescribed in situation-action terms and vice versa. They also discuss practical programming techniques that allow the advantages of declarative programming and guaranteed reactive response to be achieved simultaneously.

Rosenschein, Stanley J.↗

Photonics and other approaches to high speed communications

Our research group of 4 faculty and about 10-15 graduate students was actively involved (as a group) in the development of computer communication networks for the last five years. Many of its individuals have been involved in related research for a much longer period. The overall research goal is to extend network performance to higher data rates, to improve protocol performance at most ISO layers and to improve network operational performance. We briefly state our research goals, then discuss the research accomplishments and direct your attention to attached and/or published papers which cover the following topics: scalable parallel communications; high performance interconnection between high data rate networks; and a simple, effective media access protocol system for integrated, high data rate networks.

Maly, Kurt↗

Use of 3D vision for fine robot motion

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

Lokshin, Anatole↗

The Global Methane Budget 2000–2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4/yr (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4/yr or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4/yr or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4/yr larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4/yr larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4/yr, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30° N) compared to mid-latitudes (∼ 30 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4/yr lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4/yr by 8 Tg CH4/yr, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.

methane budget↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

A candidate concept for display of forward-looking wind shear information

A concept is proposed which integrates forward-look wind shear information with airplane performance capabilities to predict future airplane energy state as a function of range. The information could be displayed to a crew either in terms of energy height or airspeed deviations. The anticipated benefits of the proposed display information concept are: (1) a wind shear hazard product that scales directly to the performance impact on the airplane and that has intuitive meaning to flight crews; (2) a reduction in flight crew workload by automatic processing of relevant hazard parameters; and (3) a continuous display of predicted airplane energy state if the approach is continued. Such a display may be used to improve pilot situational awareness or improve pilot confidence in wind shear alerts generated by other systems. The display is described and the algorithms necessary for implementation in a simulation system are provided.

Hinton, David A.↗

System implications of large radiometric array antennas

Current radiometric earth and atmospheric sensing systems in the centimeter wavelength range generally employ a directive antenna connected through a single terminal pair to a Dicke receiver. It is shown that this approach does not lend itself to systems with greatly increased spatial resolution. Signal to noise considerations relating to antenna efficiency force the introduction of active elements at the subarray level; thus, if Dicke switching is to be used, it must be distributed throughout the system. Some possible approaches are suggested. The introduction of active elements at the subarray level is found to ease the design constraints on time delay elements, necessary for bandwidth, and on multiple beam generation, required in order to achieve sufficient integration time with high resolution.

Levis, C. A.↗