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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.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Atmospheric Escape Processes and Planetary Atmospheric Evolution: From Misconceptions to Challenges

The recent discoveries of telluric exoplanets in the habitable zone of different stars have led to questioning the nature of their atmosphere, which is required to determine their habitability. Atmospheric escape is one of the challenging problems to be solved: simply adapting what is currently observed in the solar system is doomed to fail due to the large variations in the conditions encountered around other stars. A better strategy is to evaluate the different processes that shaped planetary atmosphere and to evaluate their importance depending upon the stellar conditions. We reviewed the different escape mechanisms and their magnitude in function of different conditions [Gronoff et al. 2020]. This led us to discuss the importance of a magnetic field in protecting an atmosphere. The importance of the thermal escape, of polar wind, and of the transport of plasma within the magnetosphere are typically forgotten when claiming that magnetic fields are protecting planetary atmospheres and leading to their habitability. Overall, the habitability of a planet should not be claimed only on by its location in the habitable zone but also after careful analysis of the interaction between its atmosphere and its parent star . Gronoff, G., Arras, P., Baraka, S., Bell, J. M., Cessateur, G., Cohen, O., et al. ( 2020). Atmospheric Escape Processes and Planetary Atmospheric Evolution. Journal of Geophysical Research: Space Physics, 125, e2019JA027639. https://doi.org/10.1029/2019JA027639

G Gronoff↗
NASA NTRSDate not supplied

Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

software↗
NASA NTRSDate not supplied

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

software↗
NASA NTRS2022

Tracking the 2022 Hunga Tonga-Hunga Ha'Apai Aerosol Cloud in the Upper and Middle Stratosphere Using Space-Based Observations

On 15 January 2022, the submarine Hunga Tonga volcanic eruption lofted materials high into the upper stratosphere, reaching a record-breaking altitude of ~58 km, unprecedented in the satellite observations era. Within two weeks, the bulk of the injected material circulated the globe between 20 – 30 km altitude, as observed by satellite instruments. We estimate that the stratospheric aerosol optical depth (sAOD) is the largest since the Pinatubo eruption and is at least twice as great as the sAOD after the 2015 Calbubo eruption despite the similar SO 2 injection from that eruption. We use space-based observations to monitor the Hunga-Tonga volcanic plume evolution and transport at different altitudes as it circulates the globe. While the main aerosol layer remains trapped in the tropical pipe, small parts have already made it to both the northern and southern hemisphere poles by April, which is almost certain to influence this year's ozone hole.

Atmospheric science↗
NASA NTRS2022

Cultivating A Culture of Inclusivity in Heliophysics

The decadal survey will help guide the Heliophysics community to create opportunities for future success. A uniquely fundamental question will drive science innovations and discoveries in the coming decades: What research environment and community will we build? The most innovative scientific ideas and discoveries develop in safe, inclusive, diverse, accessible, and collaborative environments. These environments strengthen all types of collaborations and advance innovations in concepts and applications. If we ignore this critical aspect of science, current issues regarding diversity, retention, and succession will persist. This paper discusses current critical problems and introduces actionable steps that can cultivate a culture of inclusivity.

A.J. Halford↗
NASA NTRSDate not supplied

Supporting Space Weather with the Geospace Dynamics Constellation

The Geospace Dynamics Constellation (GDC) mission, planned to launch at the end of the decade, is a six-satellite constellation that will fly through the ionosphere and thermosphere at around 400 km. While GDC is a science mission, its comprehensive instrumentation will not only contribute to our understanding of space weather phenomena in the ionosphere-thermosphere system, but will also provide valuable, space weather-relevant data. Data from GDC will be made available at low latency via real-time space weather data stream. We are working with operational partners to identify space weather data products and coordinate reception of the space weather beacon data. Alongside preparations for real-time GDC data streams, we are working to identify current model capabilities and needs, to ensure that space weather models that can make use of GDC measurements are moving along the Research-toOperations pipeline. Before GDC launch, Observing System Simulation Experiments (OSSEs) carried out with synthetic GDC data can be used to demonstrate the capabilities of models and to predict the impact of GDC data. Following launch, Observing System Experiments (OSEs) will demonstrate the impact of GDC space weather data. In preparation for GDC, the ITM space weather community should establish baseline metrics for space weather parameters of scientific and operational interest. These metrics, tracked over time before and after the launch of GDC, will allow us to track advancements in forecasting, nowcasting, and hindcasting of the ITM system and to trace the impact of scientific progress from space weather research into operations. By demonstrating the impact of real-time GDC data, specific data needs can be identified and prioritized for long term investment on future observing systems.

Katherine Garcia-Sage↗
NASA NTRS2022

Investigation of the Drivers and Atmospheric Impacts of Energetic Electron Precipitation

The drivers and atmospheric impacts of energetic electron precipitation are not yet well understood. Further, electron precipitation is often poorly represented in atmospheric modeling. Additional investigations of the drivers and impacts of electron precipitation are needed to improve models and space weather forecasting requirements. To accurately represent the troposphere through the ionosphere in model simulations, it is vital to account for the chemistry accurately. Electron precipitation is a frequent, yet often ignored middle to high latitude forcing that can have dramatic effects on the middle and upper atmosphere. Over the past decade, several electron precipitation data sets have been developed, however, validation has been difficult due to the lack of independent observations of electron fluxes. Additionally, the limited number of satellites making measurements of global magnetospheric wave activity in concert with the resulting electron precipitation restricts our ability to accurately capture the drivers simultaneously with the precipitation. Accurate characterization of the drivers is needed for physics-based magnetosphere modeling. Likewise, accurate precipitating electron fluxes and relative energies are needed to improve our atmospheric modeling studies. Finally, in order to properly validate and improve our current modeling efforts, observations of atmospheric composition are necessary.

Joshua Pettit↗
NASA NTRS2022

The Importance of Policies: It’s Not Just A Pipeline Problem

For decades, a leaky pipeline analogy has been used when discussing diversity issues in STEM fields. However, this imagery is overly simplistic and does not capture critical issues that contribute to people leaving the field. It puts distance between structural issues, our actions, and why people leave the field. When we view our research structure as something more complex, we can start taking ownership and frame more impactful solutions instead of misidentifying important issues and providing ineffective short-term solutions. Many of the issues discussed in the "Cultivating a culture of inclusivity in Heliophysics" position paper have counterparts within our policies and our institutions. To fully address and mitigate the current issues within our field, we have identified a need to cultivate a positive, safe, inclusive, and effective environment. However, we need both cultural and programmatic changes. We will try to identify systemic issues that inhibit many from fully participating and potential solutions, as well as groups and fields producing best practices for creating and enabling effective environments where innovation can occur.

A.J. Halford↗
NASA NTRS2022

Kamodo’s Model-Agnostic Satellite Flythrough: Lowering the Utilization Barrier for Heliophysics Model Outputs

Heliophysics model outputs are increasingly accessible, but typically are not usable by the majority of the community unless directly collaborating with the relevant model developers. Prohibitive factors include complex file output formats, cryptic metadata, unspecified and often customized coordinate systems, and non-linear coordinate grids. Some pockets of progress exist, giving interfaces to various simulation outputs, but only for a small set of outputs and typically not with open-source, freely available packages. Additionally, the increasing array of tools built upon these sporadic interfaces are typically model-specific. We present Kamodo’s model-agnostic satellite flythrough capabilities as the solution to the utilization barrier for heliophysics model outputs. Developed at the Community Coordinated Modeling Center, these flythrough capabilities are built in Python upon a network of model-agnostic interfaces developed in collaboration with model developers, providing interpolation results the community can trust. Kamodo’s flythrough capabilities present the user with a growing variety of flythrough tools based upon a rapidly expanding library of heliophysics model outputs in several domains, currently including a variety of Ionosphere-Thermosphere-Mesosphere and global magnetosphere model outputs. Each capability is designed to be easily accessible via simplistic model-agnostic syntax, with the entire package freely available in the cloud on Github. Here, we describe the tools developed, include several sample applications for common science questions, demonstrate interoperability with selected packages, and summarize ongoing developments.

Software↗
NASA NTRSDate not supplied

SM25C-2002: Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

python↗
NASA NTRSDate not supplied

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

python↗