Climate variability and models
Climate variability and models is a research topic within Global and Planetary Change. Science Explorer counts 79k research works in it since 1950. 26.9% of them reached the world's top 10% most cited for their field and year.
This cluster of papers encompasses a wide range of research on climate change, global warming, and variability, including studies on extreme events, climate modeling, precipitation extremes, ocean circulation, ENSO variability, Arctic amplification, and the hydrological cycle. It also addresses the impact of greenhouse gas emissions and the challenge of keeping global warming below 2°C.
- Climate Change
- Global Warming
- Extreme Events
- Climate Modeling
- Precipitation Extremes
- Ocean Circulation
- ENSO Variability
- Arctic Amplification
- Hydrological Cycle
- Greenhouse Gas Emissions
- Research works
- 79k fractional, since 1950
- In the world top 10%
- 21k per year above
- Top-10% rate
- 26.9% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +30% the tick is no change
Which countries lead Climate variability and models research?
By volume, China and the United States publish the most (4.3k and 2.6k works in 2022–2025).
By volume, 2022–2025
- 1 China 4.3k works
- 2 United States 2.6k works
- 3 India 1.1k works
- 4 United Kingdom 643 works
- 5 Germany 564 works
- 6 France 470 works
- 7 Australia 364 works
- 8 Japan 336 works
- 9 South Korea 301 works
- 10 Russia 293 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Climate variability and models research?
By volume in 2022–2025, Nanjing University of Information Science and Technology publishes the most Climate variability and models research, followed by Chinese Academy of Sciences and China Meteorological Administration.
By volume, 2022–2025
- 1 Nanjing University of Information Science and TechnologyChina 343 works
- 2 Chinese Academy of SciencesChina 292 works
- 3 China Meteorological AdministrationChina 249 works
- 4 University of Chinese Academy of SciencesChina 161 works
- 5 Institute of Atmospheric PhysicsChina 154 works
- 6 Chinese Academy of Meteorological SciencesChina 121 works
- 7 Beijing Normal UniversityChina 110 works
- 8 NSF National Center for Atmospheric ResearchUnited States 96 works
- 9 Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)China 94 works
- 10 Ocean University of ChinaChina 88 works
Who are the leading researchers in Climate variability and models?
The most-cited researchers publishing on Climate variability and models include Adrian E. Raftery, Eugenia Kalnay and Ian Foster.
- 1 Adrian E. Raftery United States 5k citations
- 2 Eugenia Kalnay United States 5k citations
- 3 Ian Foster United States 4.9k citations
- 4 William D. Collins United States 4.7k citations
- 5 John E. Janowiak United States 4.6k citations
- 6 Masao Kanamitsu United States 4.5k citations
- 7 Quanan Zheng United States 4.5k citations
- 8 Susan Solomon United States 4.5k citations
- 9 Edward N. Lorenz United States 4.4k citations
- 10 Ants Leetmaa United States 4.3k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Climate variability and models research done?
The largest centres of Climate variability and models research in 2022–2025 are Beijing (China), Nanjing (China), Boulder (United States) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Tsukuba, Sparkill and Qingdao.
Largest cities, 2022–2025
Where it is the local speciality
- Tsukuba21.7 works132×
- SparkillUS · 26.7 works79×
- Qingdao31.1 works56×
- GeesthachtDE · 22.3 works35×
Location quotient: how much more of its research is in Climate variability and models than the world average.
Where is the best place to study Climate variability and models?
Among universities, judged by research, Nanjing University of Information Science and Technology, Beijing Normal University and Indian Institute of Technology Gandhinagar score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Nanjing University of Information Science and TechnologyChina | 67.6 | 17.6% | 57.6× | 343 | +158.9% |
| 2 | Beijing Normal UniversityChina | 67.3 | 34.0% | 10.8× | 110 | +104.6% |
| 3 | Indian Institute of Technology GandhinagarIndia | 62.8 | 53.4% | 7.0× | 10 | +198.9% |
| 4 | University of ExeterUnited Kingdom | 59.8 | 35.5% | 7.0× | 42 | +143.2% |
| 5 | Université Mohammed VI PolytechniqueMorocco | 59.6 | 55.4% | 7.3× | 10 | — |
| 6 | Hohai UniversityChina | 58.6 | 27.3% | 8.7× | 70 | +122.0% |
| 7 | ETH ZurichSwitzerland | 54.6 | 40.6% | 5.6× | 55 | +30.6% |
| 8 | University of ReadingUnited Kingdom | 54.3 | 24.6% | 21.9× | 62 | -8.8% |
| 9 | China University of GeosciencesChina | 54.2 | 27.7% | 6.1× | 41 | +592.0% |
| 10 | Chengdu University of Information TechnologyChina | 54.2 | 11.6% | 20.3× | 40 | +209.8% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Climate variability and models research growing?
Output in 2018–2022 was 30% higher than in 2013–2017, peaking in 2021. The fastest-growing topics are Climate variability and models.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.