Qingchen Chao

1.4k total citations · 1 hit paper
47 papers, 886 citations indexed

About

Qingchen Chao is a scholar working on Global and Planetary Change, Atmospheric Science and Sociology and Political Science. According to data from OpenAlex, Qingchen Chao has authored 47 papers receiving a total of 886 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Global and Planetary Change, 12 papers in Atmospheric Science and 6 papers in Sociology and Political Science. Recurrent topics in Qingchen Chao's work include Climate variability and models (18 papers), Climate Change and Health Impacts (6 papers) and Meteorological Phenomena and Simulations (6 papers). Qingchen Chao is often cited by papers focused on Climate variability and models (18 papers), Climate Change and Health Impacts (6 papers) and Meteorological Phenomena and Simulations (6 papers). Qingchen Chao collaborates with scholars based in China, United States and United Kingdom. Qingchen Chao's co-authors include Aiqing Feng, Rui Chang, Lin Zhao, Yongxiang Zhang, Lei Huang, Yang Wang, Guofu Wang, Zheng Wang, Yang Wang and Jinlong Huang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Qingchen Chao

45 papers receiving 853 citations

Hit Papers

Potential contributions of wind and solar power to China'... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qingchen Chao China 14 326 163 154 138 131 47 886
Sietske van der Sluis Netherlands 4 368 1.1× 224 1.4× 267 1.7× 85 0.6× 65 0.5× 5 932
Olivier Dessens United Kingdom 19 446 1.4× 146 0.9× 169 1.1× 289 2.1× 126 1.0× 30 1.0k
Bryan K. Mignone United States 18 254 0.8× 205 1.3× 254 1.6× 112 0.8× 171 1.3× 45 953
Torben K. Mideksa Norway 12 155 0.5× 101 0.6× 246 1.6× 80 0.6× 164 1.3× 26 767
Laura Cozzi Italy 7 312 1.0× 271 1.7× 315 2.0× 95 0.7× 95 0.7× 19 1.2k
Jared Creason United States 13 248 0.8× 282 1.7× 410 2.7× 84 0.6× 105 0.8× 24 938
Peter Kolp Austria 9 158 0.5× 184 1.1× 260 1.7× 70 0.5× 148 1.1× 13 728
Mukesh Gupta Canada 12 222 0.7× 211 1.3× 65 0.4× 169 1.2× 38 0.3× 36 741
Guido Franco United States 12 446 1.4× 110 0.7× 88 0.6× 273 2.0× 80 0.6× 23 828
M. Bočkarjova Netherlands 8 422 1.3× 51 0.3× 101 0.7× 106 0.8× 83 0.6× 19 860

Countries citing papers authored by Qingchen Chao

Since Specialization
Citations

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

Fields of papers citing papers by Qingchen Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingchen Chao

This figure shows the co-authorship network connecting the top 25 collaborators of Qingchen Chao. A scholar is included among the top collaborators of Qingchen Chao 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 Qingchen Chao. Qingchen Chao 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.
Tan, Xianchun, Zhe Peng, Yi Wang, et al.. (2025). Leveraging artificial intelligence for research and action on climate change: opportunities, challenges, and future directions. Science Bulletin. 70(17). 2886–2893.
2.
Chen, Lei, Xiaohui Zhong, Hao Li, et al.. (2024). A machine learning model that outperforms conventional global subseasonal forecast models. Nature Communications. 15(1). 6425–6425. 35 indexed citations
3.
Liu, Fei, B. Wang, Jeremy Cheuk‐Hin Leung, et al.. (2024). Opportunities and Barriers for Skillful Subseasonal Prediction of East Asian Summer Precipitation. Bulletin of the American Meteorological Society. 105(11). E2216–E2230. 11 indexed citations
4.
Sun, Jingbo, et al.. (2024). The energy security risk assessment of inefficient wind and solar resources under carbon neutrality in China. Applied Energy. 360. 122889–122889. 25 indexed citations
5.
Wu, Jie, Hong‐Li Ren, Jingpeng Liu, et al.. (2024). Verification of Seasonal Prediction by the Upgraded China Multi-Model Ensemble Prediction System (CMMEv2.0). Journal of Meteorological Research. 38(5). 880–900. 2 indexed citations
6.
Feng, Aiqing, Qingchen Chao, Lulu Liu, et al.. (2024). Will the 2022 compound heatwave–drought extreme over the Yangtze River Basin become Grey Rhino in the future?. Advances in Climate Change Research. 15(3). 547–556. 5 indexed citations
7.
Tang, Yuqi, Tingting Li, Xiu‐Qun Yang, et al.. (2023). Mango‐GPP: A Process‐Based Model for Simulating Gross Primary Productivity of Mangrove Ecosystems. Journal of Advances in Modeling Earth Systems. 15(12). 8 indexed citations
8.
Lu, Shuai, Xuejiao Liu, Yanlin Niu, et al.. (2023). Short-term effect of apparent temperature on daily hospitalizations for osteoporotic fractures in Beijing, China: A retrospective observational study. The Science of The Total Environment. 874. 162583–162583. 3 indexed citations
9.
Liu, Bingsheng, et al.. (2022). Feature extraction and classification of climate change risks: a bibliometric analysis. Environmental Monitoring and Assessment. 194(7). 495–495. 8 indexed citations
10.
Wang, Yang, Qingchen Chao, Lin Zhao, & Rui Chang. (2022). Assessment of wind and photovoltaic power potential in China. 1(1). 72 indexed citations
12.
Zhang, Yongxiang, Lei Huang, Qingchen Chao, Qingwen Yang, & Chao Chen. (2021). Analysis of gender equality in climate governance. Chinese Journal of Population Resources and Environment. 19(1). 98–103. 3 indexed citations
13.
Huang, Lei, et al.. (2020). The main content and insights of IPCC special report on the ocean and cryosphere in a changing climate (SROCC). Advances in Climate Change Research. 16(2). 133. 3 indexed citations
14.
Zhou, Tianjun, Jürg Luterbacher, Shaohong Wu, et al.. (2019). A new era of China-Germany joint research exploring the climate mystery of Earth. Science Bulletin. 64(23). 1733–1736. 1 indexed citations
15.
Chao, Qingchen & Aiqing Feng. (2018). Scientific basis of climate change and its response. SHILAP Revista de lepidopterología. 30 indexed citations
16.
Zhang, Yongxiang, et al.. (2017). The withdrawal of the U.S. from the Paris Agreement and its impact on global climate change governance. Advances in Climate Change Research. 8(4). 213–219. 84 indexed citations
17.
Chao, Qingchen, et al.. (2016). Paris Agreement: A New Start for Global Governance on Climate. Advances in Climate Change Research. 12(1). 61. 5 indexed citations
18.
Huang, Wei, et al.. (2016). Effect of urban symbiosis development in China on GHG emissions reduction. Advances in Climate Change Research. 7(4). 247–252. 23 indexed citations
19.
Chao, Qingchen, et al.. (2006). The Summary of Carbon Capture and Storage Technology and Its Impact on China. Diqiu kexue jinzhan. 21(3). 291–298. 6 indexed citations
20.
Chao, Qingchen, et al.. (2006). The ENSO Events in the Tropical Pacific and Dipole Events in the Indian Ocean. 20(2). 223–231. 9 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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