Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model

Abstract

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About

This paper, published in 1950, received 324 indexed citations. Written by Ulrich Cubasch, Klaus Hasselmann, Heinke Höck, E. Maier‐Reimer, Uwe Mikolajewicz, Benjamin D. Santer and R. Sausen covering the research area of Oceanography and Global and Planetary Change. It is primarily cited by scholars working on Global and Planetary Change (253 citations), Atmospheric Science (213 citations) and Oceanography (96 citations). Published in Climate Dynamics.

Countries where authors are citing Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model

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This map shows the geographic impact of Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model. 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 Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model more than expected).

Fields of papers citing Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model.

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/10.1007/bf00209163.

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