1st ISWAT Coronal Hole Boundary Working Team Meeting
June 30th 2021, 9am - 2pm (EDT)

Overview
When:

June 30th, 9am - 2pm (EDT)

Registration:

Click here to register for the meeting and receive the zoom link via email.

Organizers:

Martin A. Reiss

Space Research Institute IWF, Austria
martin.reiss@oeaw.ac.at

Karin Muglach

NASA Goddard Space Flight Center, USA
karin.muglach@nasa.gov

Speakers:

Format:Cooper Downs
Robert Jarolim
Shibaji Chakraborty
Jiwon Chung
C. Nick Arge
Larisza Krista

Predictive Science Inc., USA
University of Graz, Austria
Virginia Tech, USA
InSpace Co., South Korea
NASA Goddard, USA
University of Colorado, USA

Chris Lowder

Southwest Research Institute - Boulder, USA

Stephan Heinemann

Max Planck Institute, Germany

Jon Linker

Predictive Science Inc., USA

Emily Mason

NASA Goddard, USA

Michael Kirk

ASTRA, USA

Stefan Hofmeister

Columbia University, USA

Jeremy Grajeda

New Mexico State University, USA

Andrew Leisner

George Mason University, USA

Yang Zhou

University of Bath, UK

Each presentation length is 10 min talk plus 2 min for questions.

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Program
BLOCK 1, 9:00am - 10:30am (EDT)
Speaker

Title

Time

Martin Reiss (chair)

Meeting Organizer Introduction

9:00

Karin Muglach(chair)

Progress Update of the ISWAT Coronal Hole Boundary
Working Team

9:05

Cooper Downs

CHMAP: Coronal Hole Mapping and Analysis Pipeline

9:20

Robert Jarolim

CHRONNOS: Multi-channel Coronal Hole Detection
with Convolutional Neural Networks

9:32

Shibaji Chakraborty

Detection of Coronal Hole Boundaries in SDO/AIA
Images using Machine Vision

9:44

Jiwon Chung

DNN-based Coronal Hole Detection throughSegmentation

9:56

Community Q&A

time remaining

BLOCK 2, 10:45am - 12:00pm (EDT)
Speaker

Title

Time

Larisza Krista

The Evolution of Solar Coronal Holes Over Two Solar
Cycles

10:45

Chris Lowder

Coronal Hole Observer and Regional Tracker forLong-term Examination

10:57

Stephan Heinemann

Magnetic Evolution of Coronal Holes

11:09

Jon Linker

Coronal Hole Detection and Open Magnetic Flux

11:21

Emily Mason

The Other Side of the Coin: Correlating Border
Structures with Coronal Hole Boundary
Characteristics

11:33

Community Q&A

time remaining-2-

BLOCK 3, 12:30pm - 2:00pm (EDT)
Speaker

Title

Time

Michael Kirk

Comparing Polar Coronal Holes Across Missions

12:30

Stefan Hofmeister

Revised SDO/AIA Point Spread Functions to Correct
for Long-Distance Scattered Light

12:42

Jeremy Grajeda &Andrew Leisner

CHMAP: Identifying Coronal Holes in Solar
Observations and Comparing Them to Coronal Model
Predictions

12:54

Yang Zhou

Deep Learning models in confronting ADAPT andsatellite observations

1:18

Martin Reiss

Work Approach and Future Perspectives of the ISWAT
Coronal Hole Boundary Working Team

1:30

Community Q&A, Discussion, and Wrap-Up-3-time remaining

1st ISWAT Coronal Hole Boundary Working Team Meeting
Abstracts-4-

ABSTRACT - Shibaji Chakraborty
Title: Detection of Coronal Hole Boundaries in SDO/AIA Images using Machine Vision
Shibaji Chakraborty [1], Martin A. Reiss [2], and Karin Muglach [3,4][1] Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia, USA[2] Space Research Institute, IWF, Graz, Austria[3] Space Weather Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA[4] Catholic University of America, Washington, DC 20064, USA
Coronal holes are the observational manifestation of open magnetic field lines that appear as
dark regions in solar EUV imagery due to their lower density and temperature when comparedto the surrounding coronal plasma. We present an automated tool for detecting coronal holes
in multi-thermal images produced by the Atmospheric Imaging Assembly (AIA) instrument onboard NASA's Solar Dynamics Observatory. Our detection scheme exploits the sudden change
in intensity of the coronal holes relative to their neighborhood and uses lessons learned fromsolar physics research to identify coronal hole boundaries. The detection scheme relies on
contour-based image processing and probabilistic thresholding methods. The first results showthat the new scheme can accurately detect coronal holes in SDO/AIA images of the Sun.

ABSTRACT - Jiwon Chung
Title: DNN-based Coronal Hole Detection through Segmentation
Jiwon Chung [1], Sangmin Park [1], Jubhin Jeong [1], Dongyoung Kim [1], Haingja Seo [1],Myungjin Choi [1], Jae Hun Kim [2][1] InSpace Co., South Korea[2] National Radio Research Agency, Korean Space Weather Center
Detecting coronal holes is important to predicting the effect of solar activity on the magnetic
field of the Earth. Generally, the greater the size of coronal holes, the greater the impact on
Earth. Common approaches to detecting such events include manual labeling, computer
vision-based thresholding techniques, or machine learning. We have instead employed asegmentation technique through deep learning in automatic detection of the approximate
location and the size of coronal holes. The classic U-Net architecture and its variants, such as
the Attention U-Net and DeepUNet, were investigated in training separate models for coronalholes, and our main metric was the critical success rate (CSI). Several preprocessing steps
were taken when converting the solar data into usable images by the network, and the final
CSI of the trained model was calculated in units of independent objects, rather than pixels,
while taking into account the size of the target-5-

ABSTRACT - Cooper Downs
Title: CHMAP: Coronal Hole Mapping and Analysis Pipeline
Cooper Downs [1], James Turtle [1], Tamar Ervin [1], Opal Issan [1], Ronald M. Caplan [1],Jon A. Linker [1][1] Predictive Science Inc., United States
In this presentation we summarize an open source python framework for coronal hole mapping
and analysis, CHMAP, which we are currently transitioning for community release. Following
similar concepts to Caplan et al. (2016), our pipeline differs from typical detection schemes byemphasizing the full-sun, multi-spacecraft nature of the problem; aiming to capture coronalholes consistently in time as they evolve from days to weeks to several rotations. Keyelements of the pipeline include: 1) A modern database approach for handling 14+ years of
EUV imaging data and derived quantities. 2) Data-derived image corrections for center-to-limb
and inter-instrument intensity variations based on long-term, 6+ month moving averages. 3)
Flexible full-sun mapping methods and map types, including synchronic, synoptic, andtime-averaged minimum intensity merged maps. 4) A new technique to identify and track theevolution of individual coronal holes and associated patches using time-dependent clustering
methods and connectivity graphing. Examples illustrating key concepts and potential
applications of our pipeline will be shown.
ABSTRACT - Jeremy Grajeda, Andrew LeisnerTitle: CHMAP: Identifying Coronal Holes in Solar Observations and Comparing Them
to Coronal Model Predictions
Jeremy Grajeda [1], Andrew Leisner [2], Laura Boucheron [1], Michael Kirk [3], Jie Zhang[2], C. Nick Arge [4][1] New Mexico State University; [2] George Mason University; [3] ASTRA; [4] NASA/GSFC
Identifying coronal holes in solar disk images is very challenging, yet critical, as they serve asa key constraint for coronal models. In this shared talk, we discuss the Active Contours
Without Edges (ACWE) method for identifying coronal holes in EUV disk images such as thosefrom SDO/AIA and STEREO A&B. ACWE is an image segmentation technique that defines one
or more contours which separate an image into foreground and background. When adapted tocoronal hole segmentation, ACWE is first seeded with a group of initial contours consisting of
dark pixels within the solar EUV image. These initial contours are evolved, in an iterative
process, to maximize the homogeneity of segmented regions, producing a binary map ofcoronal holes in the original EUV image that is no longer defined by an intensity threshold.
ACWE was used to derive coronal hole boundaries in a set of STEREO EUVI/A, EUVI/B, andSDO/AIA disk images from January 2011. The ACWE results were then combined into global
synchronic maps using a synchronic map generating algorithm. Next, the ACWE synchronic
maps were directly compared to WSA model coronal hole predictions, where ADAPT
photospheric magnetic field maps were used as its input. This was done quantitatively by
calculating both the Jaccard index and the overlap coefficient for each set of maps.
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ABSTRACT - Stephan Heinemann
Title: Magnetic evolution of coronal holes
Stephan G. Heinemann [1], Manuela Temmer [2], Stefan J. Hofmeister [3][1] Max-Planck-Institut für Sonnensystemforschung, Göttingen, Germany[2] Institute of Physics, University of Graz, Austria[3] Columbia Astrophysics Laboratory, Columbia University, New York, USA
Understanding the evolution of coronal holes is the base on which any solar wind related
research and forecast is built. Slow and high speed stream interaction regions may deliverlarge amount of energy into the Earth's magnetosphere-thermosphere-ionosphere system,
cause geomagnetic storms, and shape interplanetary space. The open magnetic structure, its
evolution and interplay with the local and global fields strongly defines the coronal and solar
wind properties. Only by understanding these we can attempt to create a full picture of ourheliosphere. By statistically investigating the long-term evolution of 16 well observed CHs,
which are distributed in time over a full solar cycle, we aim to reveal processes that drive theobserved changes in the CH parameters. We use remote sensing image data from SDO andfocus on coronal, morphological and underlying photospheric magnetic field characteristics aswell as investigate the evolution of the associated high-speed streams from in-situ
measurements. We find that the CH area evolution mostly shows a rough trend of growing to a
maximum followed by a decay. No correlation of the area evolution to the evolution of thesigned magnetic flux and signed magnetic flux density enclosed in the projected coronal holearea was found. From this we conclude that the magnetic flux within the extracted coronal holeboundaries is not the main cause for its area evolution. Change rates of the signed meanmagnetic flux density and the signed magnetic flux are derived to be dependent on the solar
cycle rather than on the evolution of the individual CH. This clearly hints towards that the
global magnetic field gives significant contribution to the evolution of open magnetic fieldstructures on the Sun.
ABSTRACT - Stefan Hofmeister
Title: Revised SDO/AIA Point Spread Functions to Correct for Long-Distance
Scattered Light
S.J. Hofmeister [1], M. Hahn [1], D.W. Savin [1][1] Columbia Astrophysics Laboratory, Columbia University, New York, NY, USA
The Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO) is one of
the most-used data sources in solar physics. Its point spread functions (PSF) were wellcalibrated by the instrument team, and allows high-quality observations of the solar corona at
a resolution of ~1.5 arcsec for quiet Sun and active regions. However, it is suspected that
low-emission features such as coronal holes still contain a significant contribution of diffusive,
long-distance scattered light due to the microroughness of the mirrors, which is not accounted
for by the PSFs provided by the instrument team. We develop a novel analytical technique thatuses eclipse images and enables us to update the existing PSFs for diffusively scattered light.
No preexisting knowledge on the shape of the missing part of the PSF is required. Applying thistechnique to the point spread functions provided by the instrument team, combined with-7-

analyzing 50 partial solar eclipses, shows that an additional 5% of the light is scattered farther
away than 100 arcsec. These missing 5% have a noticeable effect for structures significantly
brighter than the quiet Sun, and a significant effect on features that are substantially darker
than the average quiet Sun. The intensity of bright structures, such as active regions, isincreased by an additional 5% as compared to the AIA images deconvolved with the original
PSFs. The intensity of dark structures, such as coronal holes, is decreased by about 40% ascompared to images deconvolved with the original PSFs. Our results demonstrate that for dark
structures such as coronal holes, coronal dimmings, and filament channels, taking into accountand correcting for the long-distance scattered light is essential.
ABSTRACT - Robert Jarolim
Title:CHRONNOS: Multi-channel coronal hole detection with convolutional neuralnetworks.
Robert Jarolim [1], A. Veronig [1,2], S. Hofmeister [3], S. G. Heinemann [4], M. Temmer[1], T. Podladchikova [5], and K. Dissauer [1,6][1] Institute of Physics, University of Graz, Austria[2] Kanzelhöhe Observatory for Solar and Environmental Research, University of Graz, Austria[3] Columbia Astrophysics Laboratory, Columbia University, 550 West 120th Street, New York,NY 10027, USA[4] Max-Planck-Institut für Sonnensystemforschung, Justus-von-Liebig-Weg 3, 37077
Göttingen, Germany[5] Skolkovo Institute for Science and Technology, Moscow, Russia[6] NorthWest Research Associates, 3380 Mitchell Ln, Boulder, CO 80301, USA
Abstract:
We present a novel fully automatic method for coronal hole detection,that provides reliable
full-disk segmentation maps and can perform in real-time. We use a convolutional neuralnetwork to identify the boundaries of coronal holes from the seven EUV channels of the
Atmospheric Imaging Assembly (AIA) as well as from line-of-sight magnetograms from the
Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). For
our primary model (Coronal Hole RecOgnition Neural Network Over multi-Spectral-data;
CHRONNOS), we use a progressively growing network approach that allows for efficienttraining, provides detailed segmentation maps and takes relations across the full solar-disk
into account. We provide a thorough evaluation for performance, reliability and consistency bycomparing the model results to an independent manually curated test set. The evaluation overalmost the full solar cycle no. 24 shows that CHRONNOS provides reliable and consistentdetections, independent of the solar activity. In addition, we train our model to identify coronalholes from each channel separately and show that segmentation maps can be also obtained
solely from line-of-sight magnetograms. We conclude with an outlook on the future plans of
the CHRONNOS project. (article status: accepted by A&A)

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ABSTRACT - Michael S.F. Kirk
Title: Comparing Polar Coronal Holes Across Missions
Michael S.F. Kirk [1,2], W.Dean Pesnell [2], C. Nickolos Arge [2], Matthew J. West [3],Raphael Attíe [4,2][1] ASTRA; [2] NASA/GSFC; [3] SWRI; [4] GMU
Comparing coronal hole features between missions is difficult because of systematic
uncertainties between how detectors image the sun. PROBA2’s SWAP instrument images thefull-disk EUV Sun using a CMOS-APS detector with a filter centered on 174 Å pass-band at a
cadence of 1-2 minutes. In contrast, the AIA instrument on SDO has a band-pass filter
centered on 171 Å and uses a CCD detector to make full-disk observations of the EUV corona.
The images these two telescope designs produce are visually quite similar in active regions,coronal loops, and the quiet corona. Polar coronal holes are the longest-lived features on thesun and are a critical piece to understand the global state of the solar corona, but because ofan oblique viewing angle, obstruction due to the coronal plasma scale height, and lack ofground truth magnetic field measurements make reliable segmentation of polar holes difficult.
We use perimeter tracing to make consistent measurements of a polar hole’s perimeter andarea in both SWAP 174 Å and AIA 171 Å images. The generated time-series of coronal holeparameters rarely agree with each other. Direct comparison of polar hole measurements
generated by these two imagers allows us to simultaneously analyze the physical properties ofpolar coronal holes and to identify systematic differences between the two different
instruments.
ABSTRACT - Larisza Krista
Title: The Evolution of Solar Coronal Holes Over Two Solar Cycles
Larisza Krista [1,2][1] Cooperative Institute for Research in Environmental Sciences, University of Colorado,
Boulder, CO 80309, USA[2] National Centers for Environmental Information, National Oceanic and Atmospheric
Administration, Boulder, CO 80305, USA
Combined data from the Solar Heliospheric Observatory (SOHO) and Solar Dynamics
Observatory (SDO) provides us with a unique opportunity to study the evolution of solar
phenomena over a period of 24 years and two solar cycles. Here, we present the results fromthe analysis of solar coronal holes observed almost every single day over two decades. An
updated version of the Coronal Hole Automated Recognition and Monitoring (CHARM) tool wasused to identify coronal holes using extreme ultraviolet observations and magnetograms. By
identifying coronal holes and measuring their physical properties in a consistent manner, wewere able to improve our understanding of their evolution over the solar activity cycle.
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ABSTRACT - Jon Linker
Title: Coronal Hole Detection and Open Magnetic Flux
Jon Linker [1], and ISSI Open Flux Team
[1] Predictive Science, Inc., United States
We report on results from our International Space Science Institute (ISSI) study, Magnetic
Open Flux And Solar Wind Structuring Of Interplanetary Space, led by Manuela Temmer, which
first met in October, 2019. We studied a low-latitude coronal hole (CH) observed on 9/19/2010
and its associated Carrington Rotation (CR2101). We investigated the uncertainties in thecalculation of open magnetic flux from remote observations by exploring the variability in the
results that occur when different CH detection techniques, different wavelengths, instruments,
and different photospheric magnetic maps, are used. As there is no "ground truth"
measurement for the open flux on the Sun, we used a thermodynamic MHD model to simulate
the corona for this time period and produced synthetic EUV emission images. The same
analysis that was performed on the observations was repeated for the simulated data, wherethe "true" open flux is known. The observational and model results were related to in-situ
estimates of the heliospheric magnetic flux. From that we assessed the overall ability ofdetection methods to account for solar open flux and identify potential sources of missing open
flux. We find that there can be considerable variability between different methods in thedetection of open field areas and open magnetic flux, and under-detection of open flux in CHs
likely contributes to the recognized deficit in solar open flux (the "Open Flux Problem").
However, it is unlikely to be the main source of the discrepancy.
ABSTRACT - Chris Lowder
Title: Coronal Hole Observer and Regional Tracker for Long-term Examination
Chris Lowder [1][1] Southwest Research Institute - Boulder, Colorado, United States
Manifesting as regions of decreased emission in extreme ultraviolet (EUV) and x-ray
wavelengths, coronal holes are the observational signatures of the roots of open solar
magnetic field. Coronal plasma within these regions is free to flow outward along open
magnetic field lines, resulting in reduced density and emission. Identifying and characterizingthese coronal hole regions provides useful insights into their connection with open magnetic
field, their evolution over the solar cycle, and impacts on space weather as a source of fastsolar wind. The Coronal Hole Observer and Regional Tracker for Long-term Examination(CHORTLE) provides an automated and adaptive tool for coronal hole detection, using an
intensity thresholding technique combined with a consideration of enclosed magnetic flux.
Utilizing EUV data from a variety of sources including SOHO/EIT, SDO/AIA, and STEREO/EUVI
A&B, coverage stretches back from solar cycle 23 to present, with multi-instrument merged
observations providing enhanced polar and far-side coverage where available. Coronal hole-10-

depth maps are generated at a variety of cadences, ranging from instantaneous snapshots toaggregate maps over solar rotation time scales. These maps are further assembled to provide
coronal hole latitudinal distributions and enclosed open magnetic flux measurements over the
span of solar cycles, yielding both a description of coronal hole evolutionary patterns and along-term set of data for comparison with both models and observations.
ABSTRACT - Emily Mason
Title: The Other Side of the Coin: Correlating Border Structures with Coronal Hole
Boundary Characteristics
Emily Mason [1,2][1] Solar Physics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA[2] Universities Space Research Associations (USRA)
Coronal hole boundaries are observationally defined by the lack of EUV emission; theclosed-field structures which border the open-field region provide the contrast for thisdefinition, as well as important local magnetic context. This study is designed to address a
critical open question: whether, and if so how, various closed structures affect the open/closed
boundary in observations. First, the full date list for the ISWAT team was assessed to classify
which structures bordered each coronal hole in the SDO/AIA field of view: helmet streamers,
pseudostreamers, active regions, and prominences/filaments. This determination was achieved
via analysis of data from SDO, STEREO, Proba2 SWAP, SOHO, MLSO K-Coronagraph, andpotential field source surface extrapolations. Using standard SunPy contouring procedures,
preliminary comparisons were made of the coronal hole boundaries in the date list using SDO
AIA 193 and 211 Å channels. This contouring method was chosen as an accessible alternative
to hand-drawing boundaries, and so that the results would not be biased towards or away fromany of the automated methods studied in Reiss et al. 2021. First-cut statistical analysis of therelative boundary locations across the various channels, categorized by bordering closed-fieldstructure, are presented here.

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ABSTRACT - Yang Zhou
Title: Deep Learning models in confronting ADAPT and satellite observations
Y. Zhou [1], S. Gonzi [2], D. Jackson [2], C. Budd [1], T. F. Haines [1], A. Majumdar [3][1] University of Bath, Dept. of Mathematical Sciences, United Kingdom[2] Met Office, United Kingdom[3] University of Strathclyde, Department of Mathematics & Statistics, United Kingdom
In my PhD work, I use deep learning tools and numerical methods to improve the accuracy of
space weather prediction models. An important intermediate model of the forecasting chain is
the Wang-Sheeley-Arge (WSA) model. But the magnetogram synoptic maps that go into WSA
have large errors. This is especially true for the representation of coronal holes (CHs). CHs are
not directly observed in the synoptic maps but are the result of a numerical minimisation
algorithm. We know there is large uncertainty in the description of the CHs that error is
propagated through WSA. One way to overcome this uncertainty is the application of theensemble method. The UK Met Office already uses ADAPT (Air Force Data Assimilative
Photospheric Flux Transport) operationally which in one way or the other gives 12 different
ensemble realisations in WSA. However, these 12 ensembles give different realisations of theCHs. In that case we lack the ground truth and it would be useful to understand which ADAPT
ensemble members have the best representation. In my first year as a PhD student, I havedeveloped a model to register satellite images and ADAPT-WSA ensemble outputs. The satellite
images were first processed with an auto-segmentation software CHIMERA (Coronal Hole
Identification via Multi-thermal Emission Recognition Algorithm). This gives me the hourly
coronal boundaries segmentation from space-borne observations. These observations areprojected onto the same coordinates, and this can allow us to compare ADAPT with satellite
images like-to-like. I will show some primary results of my research where I apply a CNNs
(Convolutional Neural Networks) based algorithm to analyse the ADAPT ensembles. Later thiswork will hopefully improve the solar wind forecast at Earth.

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