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At least 37 records · Page 2

Building Collaborative Proving Grounds for R2O2R – NASA/CCMC - NOAA/Space Weather Prediction Testbed (SWPT) Partnership

In 2016 and 2019, Executive Orders were signed by the President to prepare the Nation for Space Weather Events. At the forefront of being able to achieve this goal is the necessity to accelerate and enhance R2O2R. To drive this initiative, the Space Weather R2O2R Framework, initially led by NOAA and NASA, was developed. At the very center of the framework is the Space Weather Proving Grounds effort that will allow various institutions to collaborate, share, and advance their space weather modeling and simulation capabilities. The first of these Proving Grounds is the Architecture for Collaborative Evaluation (ACE) environment shared between the Community Coordinated Modeling Center (CCMC) at NASA and the Space Weather Prediction Testbed (SWPT) at NOAA. Since 2019, the ACE environment has been set up on the AWS cloud where it utilizes AWS cloud services and Docker containerization technology.

T. Tsui↗

Imaging Thermal He(+)in Geospace from the Lunar Surface

By mass, thermal plasma dominates near-earth space and strongly influences the transport of energy and mass into the earth's atmosphere. It is proposed to play an important role in modifying the strength of space weather storms by its presence in regions of magnetic reconnection in the dayside magnetopause and in the near to mid-magnetotail. Ionospheric-origin thermal plasma also represents the most significant potential loss of atmospheric mass from our planet over geological time. Knowledge of the loss of convected thermal plasma into the solar wind versus its recirculation across high latitudes and through the magnetospheric flanks into the magnetospheric tail will enable determination of the mass balance for this mass-dominant component of the Geospace system and of its influence on global magnetospheric processes that are critical to space weather prediction and hence to the impact of space processes on human technology in space and on Earth. Our proposed concept addresses this basic issue of Geospace dynamics by imaging thermal He(+) ions in extreme ultraviolet light with an instrument on the lunar surface. The concept is derived from the highly successful Extreme Ultraviolet imager (EUV) flown on the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) spacecraft. From the lunar surface an advanced EUV imager is anticipated to have much higher sensitivity, lower background noise, and higher communication bandwidth back to Earth. From the near-magnetic equatorial location on the lunar surface, such an imager would be ideally located to follow thermal He(+) ions to high latitudes, into the magnetospheric flanks, and into the magnetotail.

Gallagher, D. L.↗

A Multi-Year Effort to Forward the Validation of Solar Energetic Particle Prediction Models

To enable a consistent and quantitative understanding of solar energetic particle (SEP) model performance, a generalized, automated validation infrastructure, called SPHINX, is being developed by the NASA Space Radiation Analysis Group (SRAG) in close collaboration with the NASA Community Coordinated Modeling Center (CCMC), NASA Moon to Mars Space Weather Analysis Office (M2M), NOAA Space Weather Prediction Center (SWPC), and the Royal Belgian Institute for Space Aeronomy (BIRA-IASB). SPHINX is being developed to evaluate the SEP Scoreboards (https://ccmc.gsfc.nasa.gov/scoreboards/sep/), which are being used by SRAG to support space radiation operations for Mission Control. SPHINX is also being developed through a series of community challenges, which have defined a list of challenge events and a prescribed set of rules of participation. The participation of the research community has enabled the generalization of the infrastructure to validate all the types of outputs being produced by SEP models and fully exercised the framework. The most recent challenge includes 30 SEP events and 33 non-event (quiet) periods and was supported by two dedicated SEPVAL working meetings, one in the US and one in Europe (https://ccmc.gsfc.nasa.gov/community-workshops/ccmc-sepval-2023/). Here, we describe SPHINX and its interactive user interface, SPHINX-VIVID, which will eventually be made available for public use. We present selected results, outcomes, and lessons learned from the SEPVAL working meetings and validation results of the SEP Scoreboards from 2019 to present. These efforts aim to define a set of community standards for SEP model validation and describe the current state-of-the-art of SEP model performance.

Kathryn Whitman↗

The International Space Weather Initiative (ISWI)

The International Heliophysical Year (IHY) provided a successful model for the deployment of arrays of small scientific instruments in new and scientifically interesting geographic locations, and outreach. The new International Space Weather Initiative (ISWI) is designed to build on this momentum to promote the observation, understanding, and prediction space weather phenomena, and to communicate the scientific results to the public.

Davila, Joseph M.↗

Lowering Barriers to Science and Space Weather Research at the Community Coordinated Modeling Center (CCMC)

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.

space weather↗

Results from the International Heliophysical Year (IHY)

The International Heliophysical Year (IHY) involved the effort of thousands of scientists from over 70 countries, ended in February 2009. The major objectives of the IHY included over 60 collaborative studies of universal physical processes in the solar system, the deployment of arrays of small instruments to observe heliophysical processes, a unique program of educational and public outreach, and the preservation of the history of the IGY, during a two year period. A follow on effort, the International Space Weather Initiative (ISWI) is designed to build on the momentum developed during the IHY to develop the capability to observe, understand, and predict space weather phenomena.

Davila, Joseph M.↗

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗

Spacecraft Charging and Auroral Boundary Predictions in Low Earth Orbit

Auroral charging of spacecraft is an important class of space weather impacts on technological systems in low Earth orbit. In order for space weather models to accurately specify auroral charging environments, they must provide the appropriate plasma environment characteristics responsible for charging. Improvements in operational space weather prediction capabilities relevant to charging must be tested against charging observations.

Minow, Joseph I.↗

Radiation Effects on Emerging Technologies: Implications of Space Weather Risk Management

As NASA and its space partners endeavor to develop a network of satellites capable of supporting humankind's needs for advanced space weather prediction and understanding, one of the key challenges is to design a space system to operate in the natural space radiation environment In this paper, we present a description of the natural space radiation environment, the effects of interest to electronic or photonic systems, and a sample of emerging technologies and their specific issues. We conclude with a discussion of operations in the space radiation hazard and considerations for risk management.

LaBel, Kenneth A.↗

Community-Wide Validation of Geospace Model Local K-Index Predictions to Support Model Transition to Operations

We present the latest result of a community-wide space weather model validation effort coordinated among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), model developers, and the broader science community. Validation of geospace models is a critical activity for both building confidence in the science results produced by the models and in assessing the suitability of the models for transition to operations. Indeed, a primary motivation of this work is supporting NOAA/SWPCs effort to select a model or models to be transitioned into operations. Our validation efforts focus on the ability of the models to reproduce a regional index of geomagnetic disturbance, the local K-index. Our analysis includes six events representing a range of geomagnetic activity conditions and six geomagnetic observatories representing midlatitude and high-latitude locations. Contingency tables, skill scores, and distribution metrics are used for the quantitative analysis of model performance. We consider model performance on an event-by-event basis, aggregated over events, at specific station locations, and separated into high-latitude and midlatitude domains. A summary of results is presented in this report, and an online tool for detailed analysis is available at the CCMC.

Glocer, A.↗

Community-wide Validation of Geospace Model Ground Magnetic Field Perturbation Predictions to Support Model Transition to Operations

In this paper we continue the community-wide rigorous modern space weather model validation efforts carried out within GEM, CEDAR and SHINE programs. In this particular effort, in coordination among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), modelers, and science community, we focus on studying the models' capability to reproduce observed ground magnetic field fluctuations, which are closely related to geomagnetically induced current phenomenon. One of the primary motivations of the work is to support NOAA SWPC in their selection of the next numerical model that will be transitioned into operations. Six geomagnetic events and 12 geomagnetic observatories were selected for validation.While modeled and observed magnetic field time series are available for all 12 stations, the primary metrics analysis is based on six stations that were selected to represent the high-latitude and mid-latitude locations. Events-based analysis and the corresponding contingency tables were built for each event and each station. The elements in the contingency table were then used to calculate Probability of Detection (POD), Probability of False Detection (POFD) and Heidke Skill Score (HSS) for rigorous quantification of the models' performance. In this paper the summary results of the metrics analyses are reported in terms of POD, POFD and HSS. More detailed analyses can be carried out using the event by event contingency tables provided as an online appendix. An online interface built at CCMC and described in the supporting information is also available for more detailed time series analyses.

MAGNETIC↗

Three CA-Related Covariance Issues and Their Solutions

This presentation addresses three issues that arise in the use of DoD-produced satellite state estimate covariances in the conjunction assessment process: the realism of the provided covariances, how to address correlated error between two satellites' covariance matrices, and how to proceed when a furnished covariance is non-positive-definite. To address the first, DoD has implemented a set of two "consider parameters" with which to alter/expand the covariance to account for atmospheric density forecast error and satellite frontal area uncertainty, the two largest sources of unmodeled position prediction error for LEO orbits; these values are governed by a satellite's orbital parameters and ballistic coefficient histories, as well as the current and predicted space weather situation. This approach substantially improves the realism of the covariance by accounting for expected prediction errors that are not part of the fit process that generates the covariance. The second issue of covariance correlation is a complicated one, but the main shared error source—global atmospheric density error that is common to both satellites can be characterized and, through sensitivity vectors, quantified at the conjunction's time of closest approach and removed from the joint covariance, which is used in the CA probability of collision (Pc) calculation. Finally, while according to the orbit determination theory a non-positive-definite (NPD) covariance is not possible, numerical truncation and covariance interpolation can conspire to produce NPD results, which render the covariance unusable for certain CA risk assessment calculations, such as Monte Carlo Pc determination. Three similar techniques are profiled and the simplest of them recommended as a reasonable remediation technique when NPD covariances are encountered by CA practitioners.

Dynamic Consider Parameter↗

Software Displays Data on Active Regions of the Sun

The Solar Active Region Display System is a computer program that generates, in near real time, a graphical display of parameters indicative of the spatial and temporal variations of activity on the Sun. These parameters include histories and distributions of solar flares, active region growth, coronal mass ejections, size, and magnetic configuration. By presenting solar-activity data in graphical form, this program accelerates, facilitates, and partly automates what had previously been a time-consuming mental process of interpretation of solar-activity data presented in tabular and textual formats. Intended for original use in predicting space weather in order to minimize the exposure of astronauts to ionizing radiation, the program might also be useful on Earth for predicting solar-wind-induced ionospheric effects, electric currents, and potentials that could affect radio-communication systems, navigation systems, pipelines, and long electric-power lines. Raw data for the display are obtained automatically from the Space Environment Center (SEC) of the National Oceanic and Atmospheric Administration (NOAA). Other data must be obtained from the NOAA SEC by verbal communication and entered manually. The Solar Active Region Display System automatically accounts for the latitude dependence of the rate of rotation of the Sun, by use of a mathematical model that is corrected with NOAA SEC active-region position data once every 24 hours. The display includes the date, time, and an image of the Sun in H light overlaid with latitude and longitude coordinate lines, dots that mark locations of active regions identified by NOAA, identifying numbers assigned by NOAA to such regions, and solar-region visual summary (SRVS) indicators associated with some of the active regions. Each SRVS indicator is a small pie chart containing five equal sectors, each of which is color-coded to provide a semiquantitative indication of the degree of hazard posed by one aspect of the activity at the indicated location. The five aspects in question are the history of solar flares, the history of coronal mass ejections, the growth or decay of activity, the overall size, and the magnetic configuration. Mouse-clicking on an active-region-marking dot, SRVS indicator, or NOAA region number causes the program to generate a solar-region summary table (SRT) for the active region in question. The SRT contains additional quantitative and qualitative data, beyond those contained in the SRVS: These data include the solar coordinates of the region, the area of the region and its change in area during the past 24 hours, the change in the number of sunspots in the region during the past 24 hours, the magnetic configuration, and the types, dates, and times of the most recent flare and coronal mass ejection.

Golightly, Mike↗

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗

NASA Solar Sail Propulsion Technology Development

NASA's In-Space Propulsion Technology Program has developed the first generation of solar sail propulsion systems sufficient to accomplish inner solar system science and exploration missions. These first generation solar sails, when operational, will range in size from 40 meters to well over 100 meters in diameter and have an areal density of less than 13 grams per square meter. A rigorous, multi-year technology development effort culminated in 2005 with the testing of two different 20-m solar sail systems under thermal vacuum conditions. The first system, developed by ATK Space Systems of Goleta, California, uses rigid booms to deploy and stabilize the sail. In the second approach, L'Garde, Inc. of Tustin, California uses inflatable booms that rigidize in the coldness of space to accomplish sail deployment. This effort provided a number of significant insights into the optimal design and expected performance of solar sails as well as an understanding of the methods and costs of building and using them. In a separate effort, solar sail orbital analysis tools for mission design were developed and tested. Laboratory simulations of the effects of long-term space radiation exposure were also conducted on two candidate solar sail materials. Detailed radiation and charging environments were defined for mission trajectories outside the protection of the earth's magnetosphere, in the solar wind environment. These were used in other analytical tools to prove the adequacy of sail design features for accommodating the harsh space environment. Preceding and in conjunction with these technology efforts, NASA sponsored several mission application studies for solar sails. Potential missions include those that would be flown in the near term to study the sun and be used in space weather prediction to one that would use an evolved sail capability to support humanity's first mission into nearby interstellar space. This paper will describe the status of solar sail propulsion within NASA, nearterm solar sail mission applications, and near-term plans for further development.

Johnson, Les↗

Real Time Space Weather Support for Chandra X-Ray Observatory Operations

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ( soft , 100 500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth s magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA s Space Weather Prediction Center. This presentation describes the radiation mitigation strategies to minimize the proton damage in the ACIS CCD detectors and the importance of real-time data sources that are used to protect the ACIS detector system from space weather events.

O'Dell, Stephen L.↗

Multi-Spacecraft Observations of Interplanetary Shocks

Using multi-spacecraft observations primarily from ACE and WIND, and from IMP 8 and Geotail when available, the 3-dimensional structure of interplanetary shocks on the hundred Earth radii scale will be discussed. The complete magnetic field, and solar wind ion and electron data sets were used to fit the shocks with a full non-linear least squares fit "Rankine-Hugoniot" technique yielding the local shock surface normals and speeds with associated uncertainties. Multi-spacecraft results reveal that on the distance scale of ACE's L1 halo orbit the shocks deviate significantly from a simple planar geometry. This result has important consequences for the prediction of the exact arrival times of interplanetary shocks at the Earth's magnetosphere, and hence, on the reliability of space weather predictions. It also has implications on the coherence scale of solar wind structures and their evolution from the Sun to Earth.

Szabo, A.↗

Multi-Spacecraft Observations of Interplanetary Shocks

Using multi-spacecraft observations primarily from ACE and WIND and from IMP 8 and Geotail when available, the 3-dimensional structure of interplanetary shocks on the hundred Earth radii scale will be discussed. The complete magnetic field, and solar wind ion and electron data sets were used to fit the shocks with a full non-linear least squares fitting "Rankine-Hugoniot" technique yielding the local shock surface normals and speeds with associated uncertainties. Multi-spacecraft results reveal that on the distance scale of ACE's L1 halo orbit the shocks deviate from a simple planar geometry. This result has important consequences for the prediction of the exact arrival times of interplanetary shocks at the Earth's magnetosphere, and hence, on the reliability of space weather predictions. It also has implications on the coherence scale of solar wind structures and their evolution from the Sun to Earth.

Smith, C. W.↗