Turbulence and predictability in geophysical fluid dynamics and climate dynamics
Impact in
- Journal
- North-Holland eBooks
In The Last Decade
doi.org/w8243278 →Countries where authors are citing Turbulence and predictability in geophysical fluid dynamics and climate dynamics
This map shows the geographic impact of Turbulence and predictability in geophysical fluid dynamics and climate dynamics. 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 Turbulence and predictability in geophysical fluid dynamics and climate dynamics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Turbulence and predictability in geophysical fluid dynamics and climate dynamics more than expected).
Fields of papers citing Turbulence and predictability in geophysical fluid dynamics and climate dynamics
This network shows the impact of Turbulence and predictability in geophysical fluid dynamics and climate dynamics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Turbulence and predictability in geophysical fluid dynamics and climate dynamics.
About Turbulence and predictability in geophysical fluid dynamics and climate dynamics
This paper, published in 1985, received 564 indexed citations . Written by Michael Ghil, Roberto Benzi, Giorgio Parisi and Società italiana di fisica. It is primarily cited by scholars working on Economics and Econometrics (252 citations), Statistical and Nonlinear Physics (154 citations), Global and Planetary Change (148 citations), Computational Mechanics (146 citations) and Condensed Matter Physics (110 citations). Published in North-Holland eBooks.
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.
This paper is also available at doi.org/w8243278.