Amy R. Winebarger

3.5k total citations
94 papers, 2.0k citations indexed

About

Amy R. Winebarger is a scholar working on Astronomy and Astrophysics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Amy R. Winebarger has authored 94 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Astronomy and Astrophysics, 21 papers in Molecular Biology and 9 papers in Artificial Intelligence. Recurrent topics in Amy R. Winebarger's work include Solar and Space Plasma Dynamics (82 papers), Stellar, planetary, and galactic studies (54 papers) and Ionosphere and magnetosphere dynamics (26 papers). Amy R. Winebarger is often cited by papers focused on Solar and Space Plasma Dynamics (82 papers), Stellar, planetary, and galactic studies (54 papers) and Ionosphere and magnetosphere dynamics (26 papers). Amy R. Winebarger collaborates with scholars based in United States, United Kingdom and Japan. Amy R. Winebarger's co-authors include Harry P. Warren, L. Golub, J. T. Mariska, E. E. DeLuca, Steven R. Cranmer, K. Kobayashi, Jonathan Cirtain, Bart De Pontieu, R. Lionello and Z. Mikić and has published in prestigious journals such as Nature, The Astrophysical Journal and Astronomy and Astrophysics.

In The Last Decade

Amy R. Winebarger

85 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Amy R. Winebarger United States 24 1.9k 426 165 56 54 94 2.0k
P. Boerner United States 14 1.4k 0.7× 292 0.7× 175 1.1× 37 0.7× 37 0.7× 33 1.5k
C. E. DeForest United States 30 2.6k 1.4× 703 1.7× 215 1.3× 74 1.3× 55 1.0× 126 2.7k
Mark Weber United States 22 1.9k 1.0× 364 0.9× 224 1.4× 62 1.1× 70 1.3× 40 2.0k
Jonathan Cirtain United States 22 1.8k 1.0× 385 0.9× 164 1.0× 59 1.1× 36 0.7× 52 1.8k
Noriyuki Narukage Japan 18 1.3k 0.7× 265 0.6× 83 0.5× 58 1.0× 50 0.9× 59 1.3k
Paola Testa United States 25 1.8k 1.0× 220 0.5× 137 0.8× 54 1.0× 57 1.1× 77 1.9k
Katharine K. Reeves United States 27 2.2k 1.2× 418 1.0× 160 1.0× 78 1.4× 40 0.7× 99 2.2k
T. D. Tarbell United States 21 1.8k 1.0× 404 0.9× 227 1.4× 55 1.0× 71 1.3× 51 1.9k
Yoichiro Hanaoka Japan 19 1.2k 0.7× 289 0.7× 107 0.6× 78 1.4× 85 1.6× 86 1.3k
E. Khomenko Spain 28 2.1k 1.1× 524 1.2× 171 1.0× 127 2.3× 140 2.6× 118 2.3k

Countries citing papers authored by Amy R. Winebarger

Since Specialization
Citations

This map shows the geographic impact of Amy R. Winebarger's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Amy R. Winebarger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amy R. Winebarger more than expected).

Fields of papers citing papers by Amy R. Winebarger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amy R. Winebarger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Amy R. Winebarger. The network helps show where Amy R. Winebarger may publish in the future.

Co-authorship network of co-authors of Amy R. Winebarger

This figure shows the co-authorship network connecting the top 25 collaborators of Amy R. Winebarger. A scholar is included among the top collaborators of Amy R. Winebarger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Amy R. Winebarger. Amy R. Winebarger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Alemán, Tanausú del Pino, J. Trujillo Bueno, R. Ishikawa, et al.. (2025). Determining the Magnetic Field of Active Region Plages Using the Whole CLASP2/2.1 Spectral Window. The Astrophysical Journal. 991(2). 164–164.
2.
Winebarger, Amy R., et al.. (2025). Abundance Diagnostics from a Slitless Imaging Spectrometer: A Proof-of-concept for MaGIXS-2. The Astrophysical Journal. 991(2). 171–171.
3.
Athiray, P. S., et al.. (2025). A Systematic Study of Inverting Overlappograms: MaGIXS—A Case Study. The Astrophysical Journal. 980(1). 100–100. 1 indexed citations
4.
Ugarte‐Urra, Ignacio, Peter R. Young, David H. Brooks, et al.. (2023). The case for solar full-disk spectral diagnostics: Chromosphere to corona. Frontiers in Astronomy and Space Sciences. 9. 2 indexed citations
5.
6.
Warren, Harry P., Jeffrey W. Reep, Ignacio Ugarte‐Urra, et al.. (2020). Observation and Modeling of High-temperature Solar Active Region Emission during the High-resolution Coronal Imager Flight of 2018 May 29. The Astrophysical Journal. 896(1). 51–51. 11 indexed citations
7.
Schmit, D. J., Bart De Pontieu, Amy R. Winebarger, Laurel Rachmeler, & Adrian Daw. (2020). Understanding the Structure of Rapid Intensity Fluctuations in the Chromosphere with IRIS. The Astrophysical Journal. 889(2). 112–112. 3 indexed citations
8.
Golub, L., Peter Cheimets, E. E. DeLuca, et al.. (2020). EUV imaging and spectroscopy for improved space weather forecasting. Journal of Space Weather and Space Climate. 10. 37–37. 15 indexed citations
9.
Kankelborg, C. C., J. D. Parker, R. L. Smart, et al.. (2019). First Flight of the EUV Snapshot Imaging Spectrograph. AGU Fall Meeting Abstracts. 2019. 1 indexed citations
10.
Yoshida, Masaki, Y. Suematsu, R. Ishikawa, et al.. (2019). High-frequency Wave Propagation Along a Spicule Observed by CLASP. The Astrophysical Journal. 887(1). 2–2. 11 indexed citations
11.
Tiwari, Sanjiv K., et al.. (2018). Critical Magnetic Field Strengths for Solar Coronal Plumes in Quiet Regions and Coronal Holes?. The Astrophysical Journal. 861(2). 111–111. 5 indexed citations
12.
Winebarger, Amy R., R. Lionello, Cooper Downs, Z. Mikić, & J. A. Linker. (2018). Identifying Observables That Can Differentiate Between Impulsive and Footpoint Heating: Time Lags and Intensity Ratios. The Astrophysical Journal. 865(2). 111–111. 11 indexed citations
13.
Tiwari, Sanjiv K., J. K. Thalmann, Navdeep K. Panesar, Ronald L. Moore, & Amy R. Winebarger. (2017). New Evidence that Magnetoconvection Drives Solar–Stellar Coronal Heating. The Astrophysical Journal Letters. 843(2). L20–L20. 18 indexed citations
14.
Pontin, D. I., Miho Janvier, Sanjiv K. Tiwari, et al.. (2017). Observable Signatures of Energy Release in Braided Coronal Loops. The Astrophysical Journal. 837(2). 108–108. 33 indexed citations
15.
Ishikawa, Shin-­nosuke, Masahito Kubo, Yukio Katsukawa, et al.. (2017). CLASP/SJ Observations of Rapid Time Variations in the Lyα Emission in a Solar Active Region. The Astrophysical Journal. 846(2). 127–127. 4 indexed citations
16.
Winebarger, Amy R., R. Lionello, Cooper Downs, et al.. (2016). AN INVESTIGATION OF TIME LAG MAPS USING THREE-DIMENSIONAL SIMULATIONS OF HIGHLY STRATIFIED HEATING. The Astrophysical Journal. 831(2). 172–172. 11 indexed citations
17.
Tiwari, Sanjiv K., et al.. (2016). Hi-C OBSERVATIONS OF SUNSPOT PENUMBRAL BRIGHT DOTS. The Astrophysical Journal. 822(1). 35–35. 9 indexed citations
18.
Peter, Hardi, Sven Bingert, J. A. Klimchuk, et al.. (2013). Structure of solar coronal loops: from miniature to large-scale. Springer Link (Chiba Institute of Technology). 49 indexed citations
19.
Winebarger, Amy R., et al.. (2010). Electric Redshift in Jordan and Einstein Frames. AAS. 215. 1 indexed citations
20.
Winebarger, Amy R., Harry P. Warren, & J. T. Mariska. (2003). Observing the Dynamic Corona: Diagnostics to Determine Coronal Heating. 34. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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