Song Yang

11.8k total citations · 2 hit papers
303 papers, 7.4k citations indexed

About

Song Yang is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Song Yang has authored 303 papers receiving a total of 7.4k indexed citations (citations by other indexed papers that have themselves been cited), including 267 papers in Global and Planetary Change, 252 papers in Atmospheric Science and 109 papers in Oceanography. Recurrent topics in Song Yang's work include Climate variability and models (258 papers), Meteorological Phenomena and Simulations (165 papers) and Oceanographic and Atmospheric Processes (94 papers). Song Yang is often cited by papers focused on Climate variability and models (258 papers), Meteorological Phenomena and Simulations (165 papers) and Oceanographic and Atmospheric Processes (94 papers). Song Yang collaborates with scholars based in China, United States and Hong Kong. Song Yang's co-authors include Ziqian Wang, Yuan Yuan, Xingwen Jiang, Pingping Xie, Akiyo Yatagai, Tadahiro Hayasaka, Mingyue Chen, Changming Liu, Yoshihiro Fukushima and Zhenning Li and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of Geophysical Research Atmospheres.

In The Last Decade

Song Yang

279 papers receiving 7.3k citations

Hit Papers

A Gauge-Based Analysis of Daily Precipitation over East Asia 2007 2026 2013 2019 2007 2023 250 500 750

Peers

Song Yang
Comparison fields: 5 of 127
  • Global and Planetary Change 6.2k
  • Atmospheric Science 5.8k
  • Oceanography 1.9k
  • Environmental Engineering 481
  • Water Science and Technology 426
Replace Carolina Vera with:
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Richard J. Matear Australia
Boyin Huang United States
Christopher J. Merchant United Kingdom
Wanqiu Wang United States
Paul R. Halloran United Kingdom
Sang‐Wook Yeh South Korea
James D. Scott United States
Carolina Vera Argentina View profile →
Citations per field, relative to Song Yang
Song Yang · 1×
Citations per year, relative to Song Yang
Song Yang · 1×

Countries citing papers authored by Song Yang

Since Specialization
Citations

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

Fields of papers citing papers by Song Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Song Yang. A scholar is included among the top collaborators of Song Yang 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 Song Yang. Song Yang 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
# Work Indexed citations
1 0
2 1
3 0
4 0
5 1
6 1
7 15
8 9
9 0
10 4
11 1
12 2
13 14
14 0
15 5
16 4
17
Different mechanisms for the extremely hot central-eastern China in July–August 2022 from a Eurasian large-scale circulation perspective breakdown →
118
18 1
19 12
20 64

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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