3D Realistic Modeling of the Sun and Solar-type Stars to Support Disk-Integrated Observations
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In this study, we present a survey of energetic proton observations associated with Io’s footprint tail (FPT) and compare their signatures with in situ measurements of the plasma waves and lower-energy electron environments. We find further supporting evidence that proton acceleration in Io’s FPT is likely a consequence of wave–particle interactions via electromagnetic ion cyclotron waves that are generated by precipitating electrons into Jupiter’s ionosphere. This idea was originally proposed by Clark et al. (2020) and Sulaiman et al. (2020) based on NASA’s Juno mission likely transiting Io’s Main Alfvén Wing (MAW) during its twelfth orbit (i.e., PJ12). Additionally, the analysis of > 50 keV protons presented here highlights important observational details about the Io–Jupiter interaction as follows: 1) proton acceleration in Io’s FPT is a persistent feature and the energy flux carried by the protons is highest at smaller Io-Alfvén tail distances; 2) energetic protons exhibit positive correlations with both plasma waves and <100 keV/Q electrons; 3) during a small number of Io FPT crossings, the protons display finer spatial/temporal structure reminiscent of the electron observations reported by Szalay et al. (2018); and 4) the proton pitch angle distributions are characterized by two types: conic distributions in or near Io’s MAW and isotropic elsewhere.
The Starlink satellites launched on 3 February 2022 were lost before they fully arrived in their designated orbits. The loss was attributed to two moderate geomagnetic storms that occurred consecutively on February 3-4. We investigate the thermospheric neutral mass density variation during these storms with the Multiscale Atmosphere-Geospace Environment (MAGE) model, a first-principles, fully coupled geospace model. Simulated neutral density enhancements are validated by Swarm satellite measurements at the altitude of 400-500 km. Comparison with standalone TIEGCM and empirical NRLMSIS 2.0 and DTM-2012 models suggests better performance by MAGE in predicting the maximum density enhancement and resolving the gradual recovery process. Along the Starlink satellite orbit in the middle thermosphere (∼ 200 km altitude), MAGE predicts up to 150% density enhancement near the second storm peak while standalone TIEGCM, NRLMSIS 2.0 and DTM-2012 suggest only ∼ 50% increase. MAGE also suggests altitudinal, longitudinal, and latitudinal variability of storm-time percentage density enhancement due to height dependent Joule heating deposition per unit mass, thermospheric circulation changes, and travelling atmospheric disturbances. This study demonstrates that a moderate storm can cause substantial density enhancement in the middle thermosphere. Thermospheric mass density strongly depends on the strength, timing, and location of high-latitude energy input, which cannot be fully reproduced with empirical models. A physics-based, fully coupled geospace model that can accurately resolve the high-latitude energy input and its variability is critical to modeling the dynamic response of thermospheric neutral density during storm time.
Traditionally, heliophysics is characterized as the study of the near-Earth space environment, where plasmas and neutral gases originating from the Earth, the Sun, and other solar system bodies interact in ways that are detectable only through in-situ or close-range (usually within ∼10 AU) remote sensing. As a result, heliophysics has data from the space environment around a handful of solar system objects, in particular the Sun and Earth. Comparatively, astrophysics has data from an extensive array of objects, but is more limited in temporal, spatial, and wavelength information from any individual object. Thus, our understanding of planetary space environments as a complex, multi-dimensional network of specific interacting systems may in the past have seemed to have little to do with the highly diverse space environments detected through astrophysical methods. Recent technological advances have begun to bridge this divide. Exoplanetary studies are opening up avenues to study planetary environments beyond our solar system, with missions like Kepler, TESS, and JWST, along with increasing capabilities of ground-based observations. At the same time, heliophysics studies are pushing beyond the boundaries of our heliosphere with Voyager, IBEX, and the future IMAP mission. The interdisciplinary field of star-exoplanet interactions is a critical, growing area of study that enriches heliophysics. A multidisciplinary approach to heliophysics enables us to better understand universal processes that operate in diverse environments, as well as the evolution of our solar system and extreme space weather. The expertise, data, theory, and modeling tools developed by heliophysicists are crucial in understanding the space environments of exoplanets, their host stars, and their potential habitability. The mutual benefit that heliophysics and exoplanetary studies offer each other depends on strong, continuing solar system-focused and Earth-focused heliophysics studies. The heliophysics discipline requires new targeted funding to support inter-divisional opportunities, including small multi-disciplinary research projects, large collaborative research teams, and observations targeting the heliophysics of planetary and exoplanet systems. Here we discuss areas of heliophysics-relevant exoplanetary research, observational opportunities and challenges, and ways to promote the inclusion of heliophysics within the wider exoplanetary community.
What is Kamodo? -Official NASA open-source project written in Python. -Building upon the functionalization of datasets. -It is a CCMC developed and maintained software tool for access, interpolation, and visualization of space weather models and data. -It allows model developers to represent simulation results as mathematical functions which may be manipulated directly by end users. -It handles unit conversion transparency and supports interactive science discovery through jupyter notebooks with minimal coding. -All Kamodo tools are accessible through Python, and all source code is publicly available on the Kamodo NASA GitHub repositories. -Kamodo does not generate model outputs. Users need to acquire the desired model outputs before they can be functionalized by Kamodo.
Space weather models are essential to our ability to understand and predict space weather events. For over 20 years, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) has been providing transformative tools and platforms for hosting space weather models and associated services, free and open to anyone interested in studying space weather. Runs-on-Request system (ROR) is one of the popular services at CCMC that permits researchers and other end-users to exercise cutting-edge hosted heliophysics and space weather models using a simple web interface, as well as collaborate on an extensive and continuously growing archive of over 28,000 model run results. Similar to other projects at CCMC, ROR has grown as a community project that strives to be open and transparent to its users. In this poster, we discuss some of our recent efforts to further expose ROR data, metadata, and services to the end users through both custom and community-developed access protocols. We also discuss how in-house science support provided by the CCMC team plays a paramount role in making ROR data and services truly accessible by the community.
The CCMC has a diverse set of tools in many languages that support utilization of simulation outputs accessible through CCMC interactive archives. Some model output post-processing and analysis tools are delivered to tCCMC by the community. One such model output post-processing/utilization tool developed by the CCMC is the open source Kamodo package. Kamodo is developed primarily in Python (with some C) and has already established strong interoperability with other Python libraries inside PyHC and out. While that interoperability is important, interoperability with other languages and tools is as important. Many models are written in Fortran or C, and their ability to pull in data from a Python tool or export directly to other analysis software in a different language will greatly increase scientific productivity. Interoperability within Python is important, but broader interoperability is just as important.
Space weather models are essential to our ability to understand and predict space weather events. Nonetheless, some of the most cutting-edge models may struggle to move past the initial research stage, remaining unknown and inaccessible to a wider research audience, thereby hindering validation, intercomparison and adoption of the models. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) closes this gap by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a growing archive of model run results. In this presentation, we will discuss current and planned capabilities in some of the model services at CCMC, including Runs-on-Request, Instant Runs, and Real-Time Continuous Runs. We will also review new models added to the extensive collection of space weather models hosted at CCMC. Finally, we will talk about our efforts at streamlining model delivery to CCMC, including support for containerized models and establishment of an open collaborative environment based on Amazon Web Services (AWS).
Space weather models have been actively developed by the international research community, covering extensive spatial and physical domains. Still, many of the ground-breaking models remain a granular effort, insulated from a wider research audience, particularly that in different domains, and possible end users. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) seeks to remove such barriers to collaboration and coordination by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a continuously updated archive of model run results. Moreover, the multi-disciplinary science support team at CCMC facilitates and enables collaboration across domains. In our presentation, we will discuss the space weather model services at CCMC, including Runs-on-Request, Real-Time Continuous Runs, and Instant Runs. We will also review new and updated models added to the extensive collection of space weather models hosted at CCMC. We will focus on trends in model, service, and science support utilization at CCMC as a proxy to the most pressing needs of the collaborative modeling community.
The Space Weather and Heliophysics modeling community seeks to improve our understanding of space weather events and their impact on human activities. The Community Coordinated Modeling Center’s (CCMC, https://ccmc.gsfc.nasa.gov) mission is to support the community by providing a convenient collaborative platform that brings together space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. This presentation reports on CCMC’s ongoing efforts in making Heliophysics models and data more accessible, open, and reproducible. We will also explore interoperability within the ecosystem of CCMC services and how this ecosystem interoperates with external partner services and data streams.
Over the span of 20 years, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) has been leading a number of community-driven services and applications that provide a free and open access to the cutting-edge space weather and Heliophysics models through a simple web-based interface. CCMC also oversees an open archive of user model simulations and related metadata, maintains space weather-related data streams, curates validation and event datasets, and more. To maximize utility of its complementary services and data holdings, CCMC has been gradually building up an ad-hoc set of interfaces and specifications that facilitate coupling and interconnection within the organization, while also simplifying management and monitoring of the data. As the models continue to grow in maturity and complexity, CCMC is looking to reduce the complexity for its end users by making public some of the internal APIs as well as implementing dedicated interfaces as required by the community. In this presentation, we will overview the current run services at CCMC and will describe our current and near-future efforts in providing interfaces to these services.
The Space Weather and Heliophysics research and modeling community has been pushing the limits of our ability to understand and predict space weather events. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) supports the community by providing a convenient collaborative platform hosting space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. We will focus on CCMC’s ongoing commitment to the principles and guidelines of the Open Science initiative. Particularly, we will discuss our work towards making our services more transparent and our library of model simulations more accessible, open, and reproducible. We will introduce our recent tools for data discovery and correlative analysis designed to further increase the value of the user-generated data and metadata. We will also present our recent work on making heliophysical models more accessible and open to the community, particularly through simplified user experience and expert domain support. We will report on our progress in establishing an inter-center infrastructure with the ESA Virtual Space Weather Modelling Centre (VSWMC), designed to cross organizational boundaries and provide streamlined access to a joint palette of the models.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
KL extinction measurements are common in literature concerning soot producing sprays because of their nonintrusiveness. Unfortunately, these measurements often rely on bold assumptions of uniform and monodisperse spherical particles. In this work, a Spray A case is simulated using a highly detailed 3D stochastic soot model and the measured and simulated soot volume fraction are compared. Although the simulated volume fraction magnitude is approximately correct, features are much sharper than in the measured data. Optical models based on particle shape are applied to the simulated soot particles to nd the local optical thickness. The modeled optical thickness aligns with the measured volume fraction much more closely than the simulated volume fraction indicating KL extinction measurements are not simply related to soot volume fraction.