Search NASA⌕ Search

Engineering topics

MacDonald, Elizabeth A.

Publications and source records attributed to MacDonald, Elizabeth A..

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the upcoming Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science and industry and improve our readiness as a society to mitigate space weather impacts. The objective of this manuscript is to raise awareness of these concepts as we approach a solar maximum that coincides with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

A Case Study Comparing Citizen Science Aurora Data with Global Auroral Boundaries Derived from Satellite Imagery and Empirical Models

Aurorasaurus is a citizen science project that offers a new, global data source consisting of ground-based reports of the aurora. For this case study, aurora data collected during the 17-18 March 2015 geomagnetic storm are examined to identify their conjunctions with Defense Meteorological Satellite Program (DMSP) satellite passes over the high latitude auroral regions. This unique set of aurora data can provide ground-truth validation of existing auroral precipitation models. Particularly, the solar wind driven, Oval Variation, Assessment, Tracking, Intensity, and Online Nowcasting (OVATION) Prime 2013 (OP-13) model and a Kp-dependent model of Zhang-Paxton (Z-P) are utilized for our boundary validation efforts. These two similar models are compared for the first time. Global equatorward auroral boundaries are derived from the OP 13 model and the DMSP Special Sensor Ultraviolet Spectrographic Imager (SSUSI) far ultraviolet (FUV) data using the Z-P model at a fixed flux level of 0.2 erg cm(exp -2)s(exp -1). These boundaries are then compared with citizen science reports as well as with each other. Even though there are some large differences between the global boundaries for a few cases, the average difference is about 1.5 deg in geomagnetic latitude, with OP-13 being equatorward of Z-P model. When these boundaries are compared with each other as a function of local time, no clear overall trend as a function of local time was observed. It is also found that the ground based reports are more consistent with the predictions of the OP-13 model.

Kosar, Burcu C.↗
NASA NTRS2018

New Science in Plain Sight: Citizen Scientists Lead to the Discovery of Optical Structure in the Upper Atmosphere

A glowing ribbon of purple light running east-west in the night sky has recently been observed by citizen scientists. This narrow, subauroral, visible structure, distinct from the traditional auroral oval, was largely undocumented in the scientific literature and little was known about its formation. Amateur photo sequences showed colors distinctly different from common types of aurora and occasionally indicated magnetic field aligned substructures. Observations from the Swarm satellite as it crossed the arc have revealed an unusual level of electron temperature enhancement and density depletion, along with a strong westward ion flow, indicating that a pronounced subauroral ion drift (SAID) is associated with this structure. These early results suggest the arc is an optical manifestation of SAID, presenting new opportunities for investigation of the dynamic SAID signatures from the ground. On the basis of the measured ion properties and original citizen science name, we propose to identify this arc as a Strong Thermal Emission Velocity Enhancement (STEVE).

MacDonald, Elizabeth A.↗
NASA NTRS2016

Electron Dynamics in a Subproton-Gyroscale Magnetic Hole

Magnetic holes are ubiquitous in space plasmas, occurring in the solar wind, downstream of planetary bow shocks, and inside the magnetosphere. Recently, kinetic-scale magnetic holes have been observed near Earth's central plasma sheet. The Fast Plasma Investigation on NASA's Magnetospheric Multiscale (MMS) mission enables measurement of both ions and electrons with 2 orders of magnitude increased temporal resolution over previous magnetospheric instruments. Here we present data from MMS taken in Earth's nightside plasma sheet and use high-resolution particle and magnetometer data to characterize the structure of a subproton-scale magnetic hole. Electrons with gyroradii above the thermal gyroradius but below the current layer thickness carry a current sufficient to account for a 10-20 depression in magnetic field magnitude. These observations suggest that the size and magnetic depth of kinetic-scale magnetic holes is strongly dependent on the background plasma conditions.

Gershman, Daniel J.↗
NASA NTRS2015

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗