Corene J. Matyas

1.9k total citations
66 papers, 1.5k citations indexed

About

Corene J. Matyas is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Corene J. Matyas has authored 66 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Atmospheric Science, 40 papers in Global and Planetary Change and 12 papers in Oceanography. Recurrent topics in Corene J. Matyas's work include Tropical and Extratropical Cyclones Research (45 papers), Climate variability and models (35 papers) and Meteorological Phenomena and Simulations (22 papers). Corene J. Matyas is often cited by papers focused on Tropical and Extratropical Cyclones Research (45 papers), Climate variability and models (35 papers) and Meteorological Phenomena and Simulations (22 papers). Corene J. Matyas collaborates with scholars based in United States, China and South Korea. Corene J. Matyas's co-authors include Jorge Villegas, Brijesh Thapa, Ignatius Cahyanto, Sivaramakrishnan Srinivasan, Lori Pennington‐Gray, Yao Zhou, Julie A. Silva, Kevin D. Ash, Albert Robbat and Colin M. Orians and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Climate.

In The Last Decade

Corene J. Matyas

62 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Corene J. Matyas United States 22 769 751 262 203 133 66 1.5k
Chris A. Boulton United Kingdom 20 655 0.9× 217 0.3× 90 0.3× 37 0.2× 11 0.1× 57 1.6k
Jonathan A. Sullivan United States 9 688 0.9× 256 0.3× 136 0.5× 29 0.1× 16 0.1× 19 982
Sasmita Mishra India 19 186 0.2× 75 0.1× 310 1.2× 72 0.4× 9 0.1× 81 1.5k
Ting Hu China 19 1.3k 1.7× 923 1.2× 39 0.1× 108 0.5× 5 0.0× 60 1.9k
Fen Zhang China 22 545 0.7× 395 0.5× 25 0.1× 9 0.0× 88 0.7× 75 1.5k
Michael L. Grieneisen United States 24 375 0.5× 495 0.7× 55 0.2× 24 0.1× 4 0.0× 44 2.4k
Salvatore Falco Italy 14 505 0.7× 255 0.3× 97 0.4× 12 0.1× 3 0.0× 22 1.4k
Claudia Di Napoli United Kingdom 21 469 0.6× 193 0.3× 64 0.2× 16 0.1× 8 0.1× 35 1.6k
Sophie Adams Australia 12 399 0.5× 101 0.1× 245 0.9× 17 0.1× 3 0.0× 22 1.3k
Sami W. Rifai Australia 23 847 1.1× 186 0.2× 47 0.2× 11 0.1× 10 0.1× 50 1.5k

Countries citing papers authored by Corene J. Matyas

Since Specialization
Citations

This map shows the geographic impact of Corene J. Matyas'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 Corene J. Matyas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Corene J. Matyas more than expected).

Fields of papers citing papers by Corene J. Matyas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Corene J. Matyas. 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 Corene J. Matyas. The network helps show where Corene J. Matyas may publish in the future.

Co-authorship network of co-authors of Corene J. Matyas

This figure shows the co-authorship network connecting the top 25 collaborators of Corene J. Matyas. A scholar is included among the top collaborators of Corene J. Matyas 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 Corene J. Matyas. Corene J. Matyas 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
2.
Matyas, Corene J., et al.. (2024). Classification of tropical cyclone rain patterns using convolutional autoencoder. Scientific Reports. 14(1). 791–791. 5 indexed citations
3.
Park, Doo‐Sun R., et al.. (2023). Spatial Variations in Tropical Cyclone Rainfall over the Western North Pacific According to ENSO Phase. Journal of Climate. 36(6). 1697–1710. 6 indexed citations
4.
Matyas, Corene J., et al.. (2023). Evaluation of Experimental High-Resolution Model Forecasts of Tropical Cyclone Precipitation Using Object-Based Metrics. Weather and Forecasting. 38(10). 2111–2134. 5 indexed citations
5.
Matyas, Corene J., et al.. (2022). Despite challenges, 2-year college students benefit from faculty-mentored geoscience research at a 4-year university during an extracurricular program. Journal of Geoscience Education. 70(3). 354–367. 1 indexed citations
6.
Jury, Mark R. & Corene J. Matyas. (2022). Tropical cyclones in the northern Mozambique Channel: composite intra-seasonal forcing and 2019 event. Meteorology and Atmospheric Physics. 134(4). 3 indexed citations
7.
Stofer, Kathryn A., et al.. (2021). Two-Year College Students Report Multiple Benefits From Participation in an Integrated Geoscience Research, Coursework, and Outreach Internship Program. Community College Review. 49(4). 457–482. 13 indexed citations
8.
Matyas, Corene J., et al.. (2021). Geospatial Analysis of Rain Fields and Associated Environmental Conditions for Cyclones Eline and Hudah. MDPI (MDPI AG). 1(1). 92–113. 4 indexed citations
9.
Fernández-Cabán, Pedro L., et al.. (2020). Automated terrain generation for precise atmospheric boundary layer simulation in the wind tunnel. Journal of Wind Engineering and Industrial Aerodynamics. 207. 104276–104276. 30 indexed citations
10.
Kfoury, Nicole, Eric R. Scott, Colin M. Orians, et al.. (2019). Plant-Climate Interaction Effects: Changes in the Relative Distribution and Concentration of the Volatile Tea Leaf Metabolome in 2014–2016. Frontiers in Plant Science. 10. 1518–1518. 27 indexed citations
12.
Zhou, Yao & Corene J. Matyas. (2017). Spatial characteristics of storm‐total rainfall swaths associated with tropical cyclones over the Eastern United States. International Journal of Climatology. 37(S1). 557–569. 24 indexed citations
13.
Matyas, Corene J., et al.. (2016). Fast Playback Framework for Analysis of Ground-Based Doppler Radar Observations Using MapReduce Technology. Journal of Atmospheric and Oceanic Technology. 33(4). 621–634. 5 indexed citations
14.
Matyas, Corene J., et al.. (2016). A Shape Metric Methodology for Studying the Evolving Geometries of Synoptic-Scale Precipitation Patterns in Tropical Cyclones. Annals of the American Association of Geographers. 106(6). 1217–1235. 42 indexed citations
15.
Matyas, Corene J., et al.. (2015). Tropical cyclone rainfall over Puerto Rico and its relations to environmental and storm‐specific factors. International Journal of Climatology. 36(5). 2223–2237. 35 indexed citations
16.
Silva, Julie A., Corene J. Matyas, & Benedito Cunguara. (2015). Regional inequality and polarization in the context of concurrent extreme weather and economic shocks. Applied Geography. 61. 105–116. 18 indexed citations
17.
Matyas, Corene J., Sivaramakrishnan Srinivasan, Ignatius Cahyanto, et al.. (2011). Risk perception and evacuation decisions of Florida tourists under hurricane threats: a stated preference analysis. Natural Hazards. 59(2). 871–890. 102 indexed citations
18.
Matyas, Corene J.. (2008). Shape measures of rain shields as indicators of changing environmental conditions in a landfalling tropical storm. Meteorological Applications. 15(2). 259–271. 13 indexed citations
19.
Matyas, Corene J.. (2006). Analyzing Tropical Cyclone Rain Shields According to Storm Size. 1 indexed citations
20.
Matyas, Corene J.. (2006). Florida Tropical Cyclone Rainfall Totals as Related to Storm Location and Intensity. 37.

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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