Yoo‐Geun Ham

8.5k total citations · 2 hit papers
110 papers, 3.8k citations indexed

About

Yoo‐Geun Ham is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Yoo‐Geun Ham has authored 110 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Global and Planetary Change, 94 papers in Atmospheric Science and 61 papers in Oceanography. Recurrent topics in Yoo‐Geun Ham's work include Climate variability and models (99 papers), Meteorological Phenomena and Simulations (68 papers) and Oceanographic and Atmospheric Processes (56 papers). Yoo‐Geun Ham is often cited by papers focused on Climate variability and models (99 papers), Meteorological Phenomena and Simulations (68 papers) and Oceanographic and Atmospheric Processes (56 papers). Yoo‐Geun Ham collaborates with scholars based in South Korea, United States and China. Yoo‐Geun Ham's co-authors include Jong‐Seong Kug, Jeong-Hwan Kim, Jing‐Jia Luo, Fei‐Fei Jin, Jong‐Yeon Park, Soon‐Il An, June‐Yi Lee, In-Sik Kang, In‐Sik Kang and Daehyun Kim and has published in prestigious journals such as Nature, Nature Communications and Journal of Geophysical Research Atmospheres.

In The Last Decade

Yoo‐Geun Ham

102 papers receiving 3.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning for multi-year ENSO forecasts

2019 786 citations Yoo‐Geun Ham, Jeong-Hwan Kim et al. Nature profile →
Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events

2013 461 citations Yoo‐Geun Ham, Jong‐Seong Kug et al. profile →

Peers

Yoo‐Geun Ham

GPC

AS

OCEAN

EE

EEE

Youmin Tang Canada

Alberto Arribas United Kingdom

Malaquías Peña United States

Mario Marcello Miglietta Italy

Yu-Tai Hou United States

Mark Iredell United States

Len Shaffrey United Kingdom

Philippe Drobinski France

Andrea Molod United States

Huug M. van den Dool United States

Youmin Tang Canada

Yoo‐Geun Ham

2.7k ×0.8

GPC

2.4k ×0.8

AS

1.6k ×0.9

OCEAN

155 ×0.5

EE

57 ×0.6

EEE

Citations per year, relative to Yoo‐Geun Ham Yoo‐Geun Ham (= 1×) peers Youmin Tang

Countries citing papers authored by Yoo‐Geun Ham

Since Specialization

Citations

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

Fields of papers citing papers by Yoo‐Geun Ham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoo‐Geun Ham

This figure shows the co-authorship network connecting the top 25 collaborators of Yoo‐Geun Ham. A scholar is included among the top collaborators of Yoo‐Geun Ham 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 Yoo‐Geun Ham. Yoo‐Geun Ham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Kim, Hyojeong, Jin‐Soo Kim, Yoo‐Geun Ham, et al.. (2025). Anomalous temperature in North Tropical Atlantic linked to Brazilian Cerrado fires. npj Climate and Atmospheric Science. 8(1).

2.

Ham, Yoo‐Geun, et al.. (2025). Enhancing tropical cyclone track and intensity predictions with the OWZP-Transformer model. 1(1). 1 indexed citations

3.

Chang, Chih-Pei, Bin Mu, Wei Han, et al.. (2025). AI Weather and Climate Prediction and Applications. Bulletin of the American Meteorological Society. 106(12). E2571–E2578.

4.

Park, Jae‐Heung, Young‐Min Yang, Yoo‐Geun Ham, et al.. (2024). Significant winter Atlantic Niño effect on ENSO and its future projection. npj Climate and Atmospheric Science. 7(1). 3 indexed citations

5.

Jo, Hyun‐Su, et al.. (2024). Distinct Changes in the Influence of North Tropical Atlantic SST on ENSO Under Greenhouse Warming: A Comparison of CMIP5 and CMIP6. Geophysical Research Letters. 51(15). 2 indexed citations

6.

Ham, Yoo‐Geun, et al.. (2024). Few shot learning for Korean winter temperature forecasts. npj Climate and Atmospheric Science. 7(1). 1 indexed citations

7.

Ham, Yoo‐Geun, et al.. (2024). Partial-convolution-implemented generative adversarial network for global oceanic data assimilation. Nature Machine Intelligence. 6(7). 834–843. 3 indexed citations

8.

Ham, Yoo‐Geun, et al.. (2024). Distinct Propagation to Agricultural Drought Between Two Severe Meteorological Droughts in the Korean Peninsula. Geophysical Research Letters. 51(22). 1 indexed citations

9.

Yang, Young‐Min, Jeong-Hwan Kim, Jae‐Heung Park, et al.. (2023). Exploring dominant processes for multi-month predictability of western Pacific precipitation using deep learning. npj Climate and Atmospheric Science. 6(1). 6 indexed citations

10.

Jo, Hyun‐Su & Yoo‐Geun Ham. (2023). Enhanced joint impact of western hemispheric precursors increases extreme El Niño frequency under greenhouse warming. Nature Communications. 14(1). 6356–6356. 4 indexed citations

11.

Paik, Seungmok, Daehyun Kim, Soon‐Il An, & Yoo‐Geun Ham. (2023). Constraining the First Year of Ice‐Free Arctic: Importance of Regional Perspective. Earth s Future. 11(10). 1 indexed citations

12.

Ham, Yoo‐Geun, Jeong-Hwan Kim, Seung‐Ki Min, et al.. (2023). Anthropogenic fingerprints in daily precipitation revealed by deep learning. Nature. 622(7982). 301–307. 70 indexed citations

13.

Jo, Hyun‐Su, et al.. (2022). Southern Indian Ocean Dipole as a trigger for Central Pacific El Niño since the 2000s. Nature Communications. 13(1). 6965–6965. 15 indexed citations

14.

Yeh, Sang‐Wook, et al.. (2022). Present-day warm pool constrains future tropical precipitation. Communications Earth & Environment. 3(1). 13 indexed citations

15.

Kug, Jong‐Seong, Soon‐Il An, Sang‐Wook Yeh, et al.. (2021). Hysteresis of the intertropical convergence zone to CO2 forcing. Nature Climate Change. 12(1). 47–53. 68 indexed citations

16.

Ham, Yoo‐Geun, et al.. (2021). Inter‐Basin Interaction Between Variability in the South Atlantic Ocean and the El Niño/Southern Oscillation. Geophysical Research Letters. 48(15). 19 indexed citations

17.

Ham, Yoo‐Geun & Jong‐Seong Kug. (2017). ENSO amplitude changes due to greenhouse warming in CMIP5: Role of mean tropical precipitation in the 20th centur. EGUGA. 3128.

18.

An, Soon‐Il, Jong‐Seong Kug, Yoo‐Geun Ham, & Iksung Kang. (2008). ENSO modulation during a global-warming progression. AGUFM. 2008. 1 indexed citations

19.

Ham, Yoo‐Geun & In‐Sik Kang. (2008). Ensemble Kalman Filter in SNU CGCM. 한국기상학회 학술대회 논문집. 172–173. 1 indexed citations

20.

Ham, Yoo‐Geun, et al.. (2007). Impact of diurnal air-sea coupling on climate simulations. 한국기상학회 학술대회 논문집. 438–439.

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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