Changhyun Yoo

3.0k total citations · 1 hit paper
55 papers, 2.0k citations indexed

About

Changhyun Yoo is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Changhyun Yoo has authored 55 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Atmospheric Science, 47 papers in Global and Planetary Change and 16 papers in Oceanography. Recurrent topics in Changhyun Yoo's work include Climate variability and models (42 papers), Meteorological Phenomena and Simulations (21 papers) and Oceanographic and Atmospheric Processes (14 papers). Changhyun Yoo is often cited by papers focused on Climate variability and models (42 papers), Meteorological Phenomena and Simulations (21 papers) and Oceanographic and Atmospheric Processes (14 papers). Changhyun Yoo collaborates with scholars based in South Korea, United States and Taiwan. Changhyun Yoo's co-authors include Xichen Li, Sukyoung Lee, Steven B. Feldstein, Seok‐Woo Son, Edwin P. Gerber, David M. Holland, Shang‐Ping Xie, Sarah T. Gille, Seok-Woo Son and Yuna Lim and has published in prestigious journals such as Nature, Nature Communications and The Science of The Total Environment.

In The Last Decade

Changhyun Yoo

51 papers receiving 2.0k citations

Hit Papers

Atlantic-induced pan-trop... 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Changhyun Yoo South Korea 18 1.9k 1.8k 723 66 46 55 2.0k
Koutarou Takaya Japan 13 3.1k 1.7× 3.1k 1.7× 1.4k 1.9× 38 0.6× 18 0.4× 20 3.3k
Ryo Oyama Japan 8 1.3k 0.7× 1.4k 0.7× 442 0.6× 53 0.8× 16 0.3× 14 1.6k
Lukas Papritz Switzerland 20 1.1k 0.6× 1.1k 0.6× 320 0.4× 24 0.4× 28 0.6× 45 1.3k
Maria Flatau United States 22 1.3k 0.7× 1.3k 0.7× 733 1.0× 51 0.8× 38 0.8× 47 1.6k
Jonathan E. Martin United States 24 1.6k 0.8× 1.6k 0.9× 274 0.4× 45 0.7× 18 0.4× 81 1.8k
Nobutaka MANNOJI Japan 6 1.3k 0.7× 1.3k 0.7× 509 0.7× 113 1.7× 16 0.3× 7 1.6k
Carole Peubey United Kingdom 9 1.2k 0.6× 1.1k 0.6× 356 0.5× 46 0.7× 15 0.3× 12 1.4k
V. Ya. Galin Russia 16 1.3k 0.7× 1.2k 0.6× 323 0.4× 35 0.5× 19 0.4× 30 1.4k
Timothy F. Hogan United States 18 1.2k 0.6× 1.4k 0.7× 552 0.8× 162 2.5× 49 1.1× 34 1.6k
Simon P. de Szoeke United States 26 2.3k 1.2× 2.1k 1.2× 1.3k 1.9× 16 0.2× 22 0.5× 52 2.6k

Countries citing papers authored by Changhyun Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Changhyun Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Changhyun Yoo. 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 Changhyun Yoo. The network helps show where Changhyun Yoo may publish in the future.

Co-authorship network of co-authors of Changhyun Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Changhyun Yoo. A scholar is included among the top collaborators of Changhyun Yoo 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 Changhyun Yoo. Changhyun Yoo 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.
2.
Xie, Shang‐Ping, Nathaniel C. Johnson, Chunzai Wang, et al.. (2024). Unveiling the Indian Ocean forcing on winter eastern warming – western cooling pattern over North America. Nature Communications. 15(1). 9654–9654. 2 indexed citations
3.
Yoo, Changhyun, et al.. (2024). Processes Driving the Intermodel Spread of the Southern Hemisphere Hadley Circulation Expansion in CMIP6 Models. Journal of Geophysical Research Atmospheres. 129(21).
4.
Yoo, Changhyun & Sukyoung Lee. (2023). The precipitation distribution set by eddy fluxes: the case of boreal winter. npj Climate and Atmospheric Science. 6(1). 1 indexed citations
5.
Kim, Daehyun, Daehyun Kang, Min‐Seop Ahn, et al.. (2022). The Madden–Julian Oscillation in the Energy Exascale Earth System Model Version 1. Journal of Advances in Modeling Earth Systems. 14(2). 2 indexed citations
6.
Yeh, Sang‐Wook, et al.. (2022). Intrinsic atmospheric circulation patterns associated with high PM2.5 concentration days in South Korea during the cold season. The Science of The Total Environment. 863. 160878–160878. 16 indexed citations
7.
Koo, Myung‐Seo, et al.. (2021). Seasonal Performance of a Nonhydrostatic Global Atmospheric Model on a Cubed‐Sphere Grid. Earth and Space Science. 8(4). 1 indexed citations
8.
Hsu, Pang‐Chi, Hiroyuki Murakami, June‐Yi Lee, et al.. (2021). East Antarctic cooling induced by decadal changes in Madden-Julian oscillation during austral summer. Science Advances. 7(26). 19 indexed citations
9.
Son, Seok-Woo, et al.. (2021). Seesawing of Winter Temperature Extremes between East Asia and North America. Journal of Climate. 34(11). 4423–4434. 19 indexed citations
10.
Kim, Daehyun, Daehyun Kang, Min‐Seop Ahn, et al.. (2021). The Madden-Julian Oscillation in the Energy Exascale Earth System Model Version 1. 2 indexed citations
11.
Choi, Yong‐Sang, et al.. (2021). Markov Chain Analysis of Rainfall over East Asia: Unusual Frequency, Persistence, and Entropy in the Summer 2020. Asia-Pacific Journal of Atmospheric Sciences. 58(2). 281–291. 5 indexed citations
12.
Myoung, Boksoon, Jinyoung Rhee, & Changhyun Yoo. (2020). Long-Lead Predictions of Warm Season Droughts in South Korea Using North Atlantic SST. Journal of Climate. 33(11). 4659–4677. 11 indexed citations
13.
Sung, Mi‐Kyung, Changhyun Yoo, Sang‐Wook Yeh, Yu Kosaka, & Soon‐Il An. (2020). Characteristics of the North Pacific Oscillation in CMIP5 Models in Relation to Atmospheric Mean States. Journal of Climate. 33(9). 3809–3825. 11 indexed citations
14.
Sung, Mi‐Kyung, Hye-Young Jang, Baek‐Min Kim, et al.. (2019). Tropical influence on the North Pacific Oscillation drives winter extremes in North America. Nature Climate Change. 9(5). 413–418. 49 indexed citations
15.
Kim, Young‐Ha, George N. Kiladis, John R. Albers, et al.. (2019). Comparison of equatorial wave activity in the tropical tropopause layer and stratosphere represented in reanalyses. Atmospheric chemistry and physics. 19(15). 10027–10050. 16 indexed citations
16.
Choi, Yong‐Sang, et al.. (2019). Interpretation of the Top-of-Atmosphere Energy Flux for Future Arctic Warming. Scientific Reports. 9(1). 13059–13059. 8 indexed citations
17.
Koo, Ja‐Ho, Taejin Choi, Hana Lee, et al.. (2018). Total ozone characteristics associated with regional meteorology in West Antarctica. Atmospheric Environment. 195. 78–88. 4 indexed citations
18.
Son, Seok‐Woo, Yuna Lim, Changhyun Yoo, Harry H. Hendon, & Joowan Kim. (2017). Stratospheric Control of Madden-Julian Oscillation and Its Teleconnection. EGU General Assembly Conference Abstracts. 4190. 1 indexed citations
19.
Holland, David M., et al.. (2015). Rossby waves mediate impacts of tropical oceans on West Antarctic atmospheric circulation. Journal of Climate. 2 indexed citations
20.
Yoo, Changhyun, Steven B. Feldstein, & Sukyoung Lee. (2013). The prominence of a tropical convective signal in the wintertime Arctic temperature. Atmospheric Science Letters. 15(1). 7–12. 19 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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