Student Name in BOLD
Atmospheric Scale-Height via Stellar Occultations Measured By SORCE
Amelia Lee1, Joshua Elliott1, Ed Thiemann1 1Laboratory for Atmospheric and Space Physics, Boulder COPoster
The thermosphere is the uppermost layer of the atmosphere, beginning at about 100 kilometers
and ending at about 600 kilometers. At about 100 kilometers, molecular oxygen (O2) begins to break down into oxygen. We used stellar occultation scans collected from the Solar Stellar Irradiance
Comparison Experiment (SOLSTICE) instrument, on the Solar Radiation and Climate Experiment
(SORCE) satellite to look at the scale- height and density of molecular oxygen in this region. These stellar
occultations measure the irradiance of a star as it passes through the middle and lower part of the Earth’s thermosphere, from about 300km to about 20km, at a wavelength of about 140 nm in the far UV range. The measurements taken by SOLSTICE included both solar and stellar occultation scans. The
stellar occultation scans were taken as a calibration of SORCE and thus span a greater time period, and
there are many more. Irradiance values taken were in the wavelength range of 138.01 nm to 139.33 nm,
molecular oxygen absorbs these wavelengths. SOLSTICE took 818 stellar occultation scans over a seven year period between October 2003, and October 2010, which is a good portion of the solar cycle and includes a solar minimum. We present the density of molecular oxygen in the middle and lower
thermosphere and show its variability over the solar cycle.
Improved Accuracy of the Real-Time GOES-R XRS Solar Flare Location Data Product
Brooke Kotten1, Courtney Peck2,3, Janet Machol2,3, and Laurel Rachmeler3
1University of Wisconsin-Madison Department of Astronomy, 2University of Colorado Cooperative Institute for Research in Environmental Sciences (CIRES), 3NOAA National Centers for Environmental Information (NCEI)
Poster
Solar flares impact high-frequency radio communications on Earth and can be correlated with
geoeffective, or Earth-directed, coronal mass ejections (CMEs) which cause a variety of terrestrial space
weather effects. To assess these risks, the X-Ray Sensors (XRS) on Geostationary Operational
Environmental Satellites – R Series (GOES-R) measure solar X-ray irradiance and can also provide quick,
accurate, and real-time locations of solar flares with quadrant photodiodes. Our corrections improve the
XRS flare location calculation with a Monte Carlo routine that optimizes the geometric factors in the
algorithm via comparisons with locations determined using Solar Dynamics Observatory (SDO)
Atmospheric Imaging Assembly (AIA). Results from our algorithm show that the average accuracies of
M- and X-class flare locations are within 28 arcseconds. This revised method will be used to regularly
recalibrate flare locations on GOES-16, -17, and -18. The updated flare locations data product, which can
be used by space weather forecasters to assess the real-time risks to Earth, is available at
https://www.ngdc.noaa.gov/stp/satellite/goes-r.html
A New Universal Polarization Resolving Software Package for Solar Coronal and Heliospheric Observations
Bryce M Walbridge1, J. Marcus Hughes2, Matthew J. West2, Dan B. Seaton2
1Calvin University, 2Southwest Research Institute
Poster
A variety of different systems are used to characterize the degree of polarization of the visible solar corona, most prominently total brightness (B) and polarized brightness (pB). Such polarization observations allow us to analyze the background solar wind, the structure of coronal mass ejections, and their kinematics as they propagate through the heliosphere. In particular, the polarization properties of Thomson scattering yield information about the 3D location of dense features in the heliosphere. Many polarimetric instruments, such as the Solar Terrestrial Relations Observatory (STEREO) COR coronagraphs, use a symmetric three-polarizer measurement and representation system to derive the (B, pB) pair or Stokes parameters via polarization resolving software. However, only instrument-specific resolvers are available; no universal resolver exists in the commonly used Python environment. The upcoming Polarimeter to UNify the Corona and Heliosphere (PUNCH) NASA mission is one such set of instruments that will rely on a polarization resolver. Here we present a universal, open-source polarization resolver developed in Python with the PUNCH mission in mind. This resolver is capable of converting three-polarizer measurements to pB and B and vice versa. It is also capable of estimating errors as a function of photometric errors, polarizer misalignments, and polarizer effectiveness. We show the potential of the package using existing data from the STEREO mission. We test the robustness of the resolver using synthetic, forward-modeled data with the dimensions and characteristics of the PUNCH datasets. The synthetic data is produced with different noise contributions to test the ability of the resolver to construct pB and B datasets under increasingly noisy conditions and assess when data is unusable. This polarization resolver shows promise to advance our understanding of the Sun and solar wind.
Inferring Solar Lyman Beta Line Center Brightness from Band-Integrated Lyman Alpha Brightness: Correlation Studies with SOHO/SUMER and Implications for Emirates Mars
Mission
Caroline Emery1, Michael Chaffin2
1Pikes Peak Community College, 2Laboratory for Atmospheric and Space Physics
Poster
Sunlight at Lyman alpha (121.5 nm) and Lyman beta (102.6 nm) is scattered by hydrogen in the
extended Mars atmosphere, and some of this hydrogen escapes the atmosphere leading to water
loss on Mars. In order to interpret measurements of hydrogen line brightness at Mars, we need
estimates of the solar brightness at the line centers of Lyman alpha and Lyman beta. We present a
new analysis that develops a mathematical model of the relationship between the line center
brightness of these key wavelengths, and the band-integrated brightness of Lyman alpha using
full-disk solar data taken by the Solar Ultraviolet Measurement of Emitted Radiation (SUMER)
instrument on the Solar and Helioscopic Helioscopic Observatory (SOHO). Previous work
examined the relationship between these wavelengths’ line center and band-integrated
brightness. At present, the Mars Atmospheric and Volatile EvolutioN mission (MAVEN)
Extreme Ultraviolet Monitor (EUVM) instrument measures the band-integrated Lyman alpha
brightness at Mars. Some methods exist to infer the solar Lyman beta line center brightness from
this quantity, but no direct correlation study has been performed. Here, we perform this analysis
and develop a proxy for the Lyman beta line center brightness using the MAVEN EUVM Lyman
alpha measurements, enabling more accurate estimates of the solar brightness illuminating Mars’
atmosphere. We conduct research using SOHO/SUMER observations of Lyman alpha and
Lyman beta line profiles normalized to LASP Interactive Solar IrRadiance Data Center (LISIRD)
and Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission (TIMED) Solar
EUV Experiment (SEE) brightness values for these wavelengths. Using this data, we will present
scatterplots of band-integrated Lyman alpha brightness against the line center brightness of
Lyman alpha and Lyman beta, providing a new proxy for the solar Lyman beta line center
brightness that is useful at Mars.
Forwarding Modeling of Forbidden Coronal Lines in Synthetic Flares
Carter Woodson1, Tom Schad2, Dylan Kee2
1Colorado State University, 2National Solar Observatory
Poster
The energy that builds up in the coronal magnetic field configuration is the source of eruptive solar flare
events that can damage technological infrastructure on Earth. Observing polarized light from forbidden
coronal emission lines is one of the few means available for measuring the energy and configuration of
the magnetic field and may allow for remotely tracking this build-up and release of energy. This
investigation utilizes simulated Magnetohydrodynamic (MHD) values from the MPS/University of
Chicago Radiative MHD (MURaM) code along with the CHIANTI atomic database and Python package pyCELP (Tom Schad) to synthesize polarized coronal emission spectra. The simulation captures the interactions between two bipolar active regions, and the analysis captures features of the spectral emission correlating to these interactions. Our results demonstrate the relationship between the Stokes polarization parameters for the synthesized emission spectra and the regions in the simulation where these polarized signals probe most strongly. Further investigation can inform as to which techniques or instrumentation may be necessary to reliably observe polarized signals in the solar atmosphere.
Finding Better Spectral Resolution Data from SDO EVE for New Measurements of Solar Flares
Gabriela Gonzalez1, Phil Chamberlin2, Vicki Herde2
1Southern Illinois University Edwardsville, 2Laboratory for Atmospheric and Space Physics
Poster
Studying solar flare spectrum can help us work towards predicting solar flares and space weather
which affects our technology here on Earth. Using SDO EVE MEGS A2 data we are looking at
solar flare ion emission lines to measure their doppler shifts. MEGS A2 data comes in pixel units
which must be converted into wavelength values. We can’t assume the conversion from pixel to
wavelength (plate scale) is linear so we must fit the MEGS A2 data to create an accurate plate
scale. Using a Gaussian fit we found the peak locations of 12 ions during pre-flaring conditions.
This information was used to derive the nonlinear plate scale. We then subtracted the pre-flare
data from the impulse and gradual phase data of the flare to only look at ions present during a
flare. Using the newly derived plate scale, we calculated the Doppler shifts of each ion and their
associated doppler velocities. We can use this information to discover which ions are blue- and
red-shifted which may tell us at what height the magnetic reconnection of the flare occurs.
Pushing the Frontiers of Operational Geoelectric Hazard Modeling
Gabriel Moraga1, Wendy Carande2, Greg Lucas2
1University of Colorado at Boulder, 2Laboratory for Atmospheric and Space Physics
Poster
Space weather, and the effects it has on Earth, has been a recent trending topic in the
STEM world. With major solar storms affecting Earth, such as the 1989 Quebec power grid
failure, there is a growing need to accurately predict and measure the geoelectric field data.
Geoelectric hazards can critically affect infrastructure, and the aftermath are economically costly
to recover from. The push to enhance geoelectric hazard modeling, which implements a
combination of research and machine learning, is essential. Organizations such as NOAA,
USGS, NASA, NSF and international partners (NRCan) have contributed to generating an
operational geoelectric field map data product. Currently, there are 30 ground based real-time
stations across North America that measure surface geomagnetic field data that are used as input
for the geoelectric field maps. There are several interpolation methods in place, as well as
physics models that generate synthetic data and measure ionospheric conductivities. The
interpolation methods presently in use remove missing data which results in non-optimal
interpolations. One issue is that there is no machine learning method in place to fill missing data
in real time, with additionally flagging outliers. Presently, we have created an algorithm, in
Python, that will interpolate missing data and spot anomalies that are outside a standard
deviation of 3 threshold, and can be run in real-time. With the Seasonal Auto-Regressive
Integrated Moving Average (SARIMA) anomaly detection model as the base, the newly created
model will be incorporated to fill gaps and confirm anomalies. Using machine-learning
algorithms to identify and replace missing data within the real-time data streams will generate
geoelectric field maps that are accurate and clean. The end result of machine learning methods
will be run in the University of Colorado’s Space Weather Technology Research and Education
Center’s (TREC) cloud-based Testbed environment.
Solar chromospheric variability in Ha, CaII IR and CaIIK.
Garrett Zills1, Serena Criscuoli2
1Boulder Solar Alliance, 2National Solar Observatory
Poster
Understanding the long-term, chromospheric variability of the Sun is paramount to improve our
knowledge of a variety of phenomena such as, solar-dynamo processes, space weather, and the effects
the Sun has on the Earth’s atmosphere and climate. Similarly, stellar variability determines the physical
and chemical properties of exo-planets atmospheres and their habitability. While UV and shorter
wavelength chromospheric diagnostics such as the Ca II H and K index have been well studied over the
course of the solar cycle, how the longer wavelength diagnostics correlate with the shorter wavelength
diagnostics has yet to be fully explored. A deeper understanding of how the shorter and longer
wavelength diagnostics respond to magnetic activity could bridge the current information gap present on many of the newer missions that only contain longer wavelength measurements. Using data acquired
with the Integrated Sunlight Spectrometer, between 2007 and 2017, we investigated the correlation
between the CaIIK emission index and indices derived from the Ha 656.3 nm and CaII 854.2 nm lines
which are well known chromospheric diagnostics. We found that both the core intensities and core
widths of the two lines are positively correlated with the CaIIK emission index, the core width of the Ha
line showing the highest correlation, 0.85, and the other indices presenting a correlation of approximately 0.5. We also found that such correlations vary with the activity cycle, the Ha core width
showing the smallest variation (25%) and the other indices varying approximately (40%) between the minimum and maximum of the analyzed Cycle 24. These results are in qualitative agreement with previous results obtained from the analysis of spatially resolved observations and models and suggest that the Ha core width best traces chromospheric activity.
Coalignment of Skylab Imagery for CME Analysis
Huge Mettes1, Alice Lecinski2, Daniela Lacatus2
1Regis University, 2High Altitude Observatory
Poster
Our project involves the old Skylab space station, launched by NASA in 1973 and
occupied for 24 weeks. The data is collected from one of the major operations onboard, the solar
observatory that had the Apollo Telescope mount. This device captured some of our first data on
Coronal Mass Ejections (CMEs), however this data came out with some issues that made it
difficult for proper analysis. Due to the very dim corona around the sun an occulter is used to
hide the solar disk. This occulter had a pylon that could be adjusted which in some cases made
drastic inconsistencies in the images. We can see dust particles and other noise in the data.
Whilst some errors were recorded in the diode matrix on the film and corrected, there are still
unaccounted errors. Our code is designed to take the Skylab data and run it through a series of
algorithms designed to account for these issues and produce more usable data.
The images are first converted from cartesian coordinates to polar coordinate reference
frames with 0.5 degree sampling. Film irregularities are reduced greatly using “Edge_dog” filters
over a pair of sequential images. This process greatly reduces noise in the data. This is followed
by detecting the location of the pylon in each image to avoid scanning them.
With the pylons located, the pixel shift values between subsequent frames can be found
and put in a histogram.The peak of the histogram establishes the actual shift value. The accuracy
of this process is greatly improved by limiting the sample boxes in the reference image to areas
of high signal to noise. The pixel shift is converted to arcseconds and the header adjusted
accordingly. This process is run through the entire database, resulting in a new coaligned database. With the new database produced we have a series of images that can be turned into GIFs,
animations, slides, etc and used for analyzing the evolution and dynamics of CMEs. Something we have not been able to do with the Skylab data so far.
Using Power Spectral Density and a Self-Organizing-Map to Detect Precipitation Bands Observed by SAMPEX
Joann Jones1,2, Sergio Vidal-Luengo1, Lauren Blum1
1Laboratory for Atmospheric and Space Physics, 2Case Western Reserve University
Poster
Precipitation bands are a form of relativistic electron precipitation in the outer Van Allen radiation belt. They contribute significantly to the rapid loss of electrons from the outer belt, yet their origin is still unclear. In this study, we develop an algorithm to automatically detect precipitation bands observed by the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) satellite (1992-2012) using an unsupervised machine learning technique called a Self- Organizing-Map (SOM).
Investigation of Acoustic Mode Frequencies and Surface Activity over Multiple Solar Cycles
Mackenzie Baird1, Dr. Sushanta C. Tripathy2, Dr. Kiran Jain2
1Villanova University, 2National Solar Observatory
We investigate high-degree acoustic mode frequencies of the Sun and surface activity,
over the course of multiple solar cycles, to improve our understanding of the connection between
the solar interior and atmosphere. This study covers the period from July 2001 to December
2021. We focus on high-degree modes due to their ability to characterize conditions just below
the solar surface. Using the full-disk Doppler observations made by the Global Oscillation
Network Group (GONG), mode frequencies are computed through the local helioseismic
technique of ring diagrams. We further consider 10.7 cm radio flux measurements, the
international sunspot number, and the magnetic activity index (MAI) as indicators of solar
activity. Considering the entire period of 20 years, we find a strong linear correlation between the
frequency shifts and each activity indices. The strongest correlation is found between the MAI
and the frequency shifts, with a Pearson correlation coefficient of 0.96. Since the evolution of
magnetic activity is known to be asymmetric between the two hemispheres, we focus on the
relation between the hemispheric frequency shifts and the hemispheric activity indices. We
further investigate the progression of the solar cycle at different latitudes. In addition, we
examine the behavior of the quasi-biennial oscillation through a wavelet technique to assess its
presence in solar cycles 23 and 24.
Analysis of Dynamics of Ions in the Plasmasphere using a Machine Learning Model
Max Doering1,2, Xiangning Chu1, James Lende1
1LASP, University of Colorado, 2Indiana University
Poster
The plasmasphere consists of cold plasma (~1 eV) at mid-to low-L-shells surrounding the Earth. The plasma density and composition in Earth’s plasmasphere greatly influences energetic particle scattering, wave propagation and wave-particle interactions. Thus it is important to understand how the plasmasphere erodes and refills during geomagnetic events. Historically, empirical models have been linear in nature; statistical models that reflect the average behavior of the plasmasphere but cannot reflect the short-term changes in the plasmasphere during geomagnetic events. This method is also limited by the lack of spatial coverage of in-situ measurements, especially at specific local times and L-shells. In addition, these models are limited by the instrumentation capability to measure very cold ions (<1 eV). To remedy this, we employed a method to infer the density of different ion species, then we developed non-linear machine learning models of the cold plasma, including total plasma density and different ion species to produce global and time-dependent reconstructions of the plasmasphere at any time and location. For inputs, this model used Van Allen Probe data and geomagnetic indices and solar wind parameters from the OMNI dataset. We showed that the model can reproduce dynamic evolution of the cold electrons and ion species. We also investigated how ion plasmas erode and refill in response to varying levels geomagnetic activity. The effects of different drivers on the plasmaspheric dynamics are also explored. Our model will help understand the complex physics that takes place in the plasmasphere
Evaluation of Multi-Point Estimates of Magnetic Field Gradients in Near-Earth Space using
MMS Data
Mickayla Dever1, Alexandros Chasapis2, Peter Tatum2, Ramiz Qudsi3
1Central Michigan University, 2University of Colorado Boulder, 3Boston University
Poster
Using data from the Magnetospheric Multiscale (MMS) mission in 2019 that focused on the
turbulence of the solar wind and the magneto sheath, we evaluate the curl of the magnetic field
using multi-point measurements. During a period of two weeks in 2019, the four spacecraft were
in a co-linear formation that pointed along the same direction. This formation allowed for
measurements that directly relate to the method of estimating the electric current of those same
fields. Specifically with the spacecraft’s co-linear formation we can use the assumption of
linearity to better understand the turbulent fluctuations of the solar wind, the magnetic field, and
its currents. This assumption will also allow for the evaluation of the different separation and the
different conditions of the spacecrafts, permitting us to evaluate the robustness of the gradient
estimations. To do so, we use two-point measurements which can then be used to compute the
gradients of the magnetic field and then its curl. Specifically, we use the magnetic field
measurements and spacecraft position data and perform a linear interpolation between pairs of
spacecraft. For our purposes, we are focusing on one interval of five hours of burst resolution
data obtained in the near-Earth solar wind. From our examinations, we are able to measure the
accuracy of the difference between the values obtained by linear interpolation compared to the
direct measurement by that spacecraft. Furthermore, we are able to carry out a quantitative
evaluation of this deviation and perform a statistical study across the entire dataset.
IBIS Wide Field Mosaic and How We Study the Solar Magnetic Structure
Rachael Weir1, Kevin Reardon1
1NSO (National Solar Observatory)
Poster
Our sun has many different structures adorning it, some spanning hundreds of thousands of kilometers, to features that test the limits of the current resolving power of our equipment. Taking full advantage of the breadth of these structures requires a wide filed of view and high-resolution images, which to this day is still challenging. One way that we try and overcome this challenge is with solar mosaics. Combining multiple high-resolution images of the sun, taken from space telescopes and one larger lower resolution image of the sun, taken from a ground-based telescope is how we create the mosaics. Using images from the IBIS optics telescope taken in 2017 we aligned the images in a way that created a whole image of the sun that we then compared to the full disk image of the sun, thus creating the mosaic. In doing so are able to study multiple different structures of the sun, such as sunspots and granulations on the solar surface. Furthermore, we can study how these structures affect other elements of the sun. In this study we are particularly interested in the way that solar activity affects the magnetic field that is housed inside the sun’s chromosphere. The originality of our mosaics observations in particular is the way that we are able to manipulate the whole spectral information over the full field of view, and we are able to do this for multiple different spectral lines at one time. Doing this, however, does not compromise the spatial resolution of the field. This is what allows us to view fibrils of the sun, which we use to determine the magnetic field of the sun. Fibrils begin to appear when we view the mosaic in the Hα part of the spectrum. Here we are able to see the ways that solar activity fluctuates because of these fibrils, and because we assume that the fibrils align with the magnetic field of the sun, we can see the way that the magnetic field fluctuates as well. Knowing and understanding the magnetic field of the sun is incredibly valuable to us as it plays a key role in the dynamics of the solar surface.
Systematic Evaluation of the Performance
of the Robinson Conductance Formulas
Reese Van Putten1, Dr. Xiaohua Fang2, Dr. Naomi Maruyama2
1Florida Institute of Technology, 2Laboratory for Atmospheric and Space Physics, University of Colorado
Poster
The Robinson et al. (1987) empirical model has been widely applied by the space physics community to
estimate ionospheric Pedersen and Hall conductances in association with auroral electron precipitation.
Despite its application for decades, the accuracy of the formulas remains unclear. In particular, little is
known about the extent to which the conductances depend on background atmospheric, ionospheric, and geomagnetic field conditions, which were not considered in the early study. The fact that the Robinson formulas were derived from limited observations during moderate activity using a simplistic electron impact ionization model also points to the necessity of examining model accuracy in a systematic manner. In this study, four empirical models work in concert to self-consistently calculate Pedersen and Hall conductivity altitude profiles under a variety of precipitation and background conditions, during periods of both low and high geomagnetic and solar activity. Specifically, we apply the Fang et al. (2010) parameterization model to calculate the impact ionization of precipitating electrons with different energies. The Naval Research Laboratory Mass Spectrometer Incoherent Scatter radar (NRLMSIS 2.0) model is used to specify the background neutral density distributions. The International Reference Ionosphere (IRI 2016) model is used to partition the resulting electron densities among individual ion species as well as to estimate ionospheric electron and ion temperatures. The International Geomagnetic Reference Field (IGRF-13) model is employed to calculate geomagnetic fields and thus electron and ion gyrofrequencies. By applying these empirical models, we self-consistently calculate conductivities resulting from auroral electron precipitation and then obtain their altitude integral or conductances. The comparison with the prediction of the Robinson formulas allows us to systematically assess their accuracy and limitation. More importantly, our new results enable the development of a new conductance model that not only has improved accuracy but also has known errors.
Preparing for the 2024 Total Solar Eclipse with Citizen CATE
Sarah Davis1, Amir Caspi2, Dan Seaton2, Sarah Kovac2
1University of Northern Colorado, 2Southwest Research Institute
Poster
The Citizen Continental-America Telescope Eclipse (CATE) Experiment is designed to
take continuous images of the solar corona over the full duration of the 2024 total solar eclipse
across America. To achieve this, we will recruit 40 groups of citizen scientists along the path of
the eclipse in order to obtain a 60-minute uninterrupted movie of the solar corona on April 8,
2024 (18:27–19:35 UT). Using the polarization data we obtain, we will map the density
distribution of free electrons in the solar corona and study connectivity in the middle and lower
corona. During the summer of 2022, we tested various candidate observing setups that will be
distributed to citizen scientists along the path of the eclipse. Different items that we tested
include a DayStar refractor telescope, PointGrey CMOS camera, FLIR BlackFly polarizing
imager, and a diverse array of telescope accessories and software. We define a photon transfer
curve for each camera to characterize and analyze its performance and suitability for the high
dynamic range imaging required for the CATE project. We found that the telescope and
polarization camera have satisfactory performances, making them reliable candidates for the
2024 eclipse. After completing further analysis of the 2017 CATE data (see Penn et al., 2020;
DOI:10.1088/1538-3873/ab558c), we identified multiple improvements to the software and
procedures to improve data collection and quality in 2024. Other preparatory tasks completed
this summer included identifying prospective observing sites along the eclipse path and
organizing the hierarchical management structure for the project. We are organizing a workshop
for CATE volunteers and creating teaching materials with a universal curriculum to train
everyone involved with this project. This workshop will take place at Southwest Research
Institute in San Antonio, Texas in January 2023. Volunteer observers will receive educational
lectures and hands-on training with the exact equipment they will use on eclipse day. Here, we
present the results of our initial preparatory planning phase, including equipment
characterization, improvements to the software and data reduction pipeline, plans for the 2023
training workshop, and prospects for the 2024 eclipse observing campaign.