Virginie Guémas

4.5k total citations
66 papers, 2.2k citations indexed

About

Virginie Guémas is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Virginie Guémas has authored 66 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Global and Planetary Change, 56 papers in Atmospheric Science and 20 papers in Oceanography. Recurrent topics in Virginie Guémas's work include Climate variability and models (56 papers), Arctic and Antarctic ice dynamics (32 papers) and Meteorological Phenomena and Simulations (26 papers). Virginie Guémas is often cited by papers focused on Climate variability and models (56 papers), Arctic and Antarctic ice dynamics (32 papers) and Meteorological Phenomena and Simulations (26 papers). Virginie Guémas collaborates with scholars based in France, Spain and United Kingdom. Virginie Guémas's co-authors include Francisco J. Doblas‐Reyes, Javier García‐Serrano, Omar Bellprat, François Massonnet, Neven S. Fučkar, Chloé Prodhomme, Sarah Keeley, Steffen Tietsche, Geert Jan van Oldenborgh and Markus G. Donat and has published in prestigious journals such as Science, Nature Communications and Journal of Geophysical Research Atmospheres.

In The Last Decade

Virginie Guémas

65 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Virginie Guémas France 26 1.8k 1.8k 633 81 61 66 2.2k
Xichen Li China 21 1.8k 1.0× 1.8k 1.0× 819 1.3× 62 0.8× 85 1.4× 98 2.3k
E. M. Volodin Russia 22 1.5k 0.8× 1.6k 0.9× 407 0.6× 51 0.6× 84 1.4× 90 1.9k
Anthony R. Lupo United States 28 2.6k 1.4× 2.7k 1.5× 641 1.0× 153 1.9× 30 0.5× 150 3.1k
Xin Qu United States 22 1.9k 1.0× 1.8k 1.0× 217 0.3× 61 0.8× 48 0.8× 40 2.3k
Torben Koenigk Sweden 28 1.9k 1.1× 1.6k 0.9× 467 0.7× 41 0.5× 130 2.1× 68 2.2k
Camiel Severijns Netherlands 16 1.1k 0.6× 1.3k 0.7× 394 0.6× 71 0.9× 28 0.5× 24 1.6k
Yoshimitsu Chikamoto United States 23 1.7k 0.9× 2.0k 1.1× 1.2k 1.8× 49 0.6× 25 0.4× 45 2.2k
Alessio Bellucci Italy 26 2.0k 1.1× 2.3k 1.3× 903 1.4× 105 1.3× 39 0.6× 66 2.6k
Wenjun Zhang China 29 2.3k 1.2× 2.7k 1.5× 1.4k 2.1× 61 0.8× 35 0.6× 110 3.0k
Hylke de Vries Netherlands 24 1.2k 0.7× 1.3k 0.7× 350 0.6× 71 0.9× 18 0.3× 69 1.7k

Countries citing papers authored by Virginie Guémas

Since Specialization
Citations

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

Fields of papers citing papers by Virginie Guémas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Virginie Guémas

This figure shows the co-authorship network connecting the top 25 collaborators of Virginie Guémas. A scholar is included among the top collaborators of Virginie Guémas 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 Virginie Guémas. Virginie Guémas 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.
Guémas, Virginie, et al.. (2024). Reducing Parametrization Errors for Polar Surface Turbulent Fluxes Using Machine Learning. Boundary-Layer Meteorology. 190(3). 1 indexed citations
2.
Guémas, Virginie, et al.. (2023). Surface Turbulent Fluxes From the MOSAiC Campaign Predicted by Machine Learning. Geophysical Research Letters. 50(23). 3 indexed citations
3.
Materia, Stefano, Constantin Ardilouze, Rachel H. White, et al.. (2021). Seasonal prediction of European Summer Heatwaves. 6 indexed citations
4.
Navarro, Juan C. Acosta, Pablo Ortega, Lauriane Batté, et al.. (2020). Link Between Autumnal Arctic Sea Ice and Northern Hemisphere Winter Forecast Skill. Geophysical Research Letters. 47(5). 12 indexed citations
5.
Bellprat, Omar, Virginie Guémas, Francisco J. Doblas‐Reyes, & Markus G. Donat. (2019). Towards reliable extreme weather and climate event attribution. Nature Communications. 10(1). 1732–1732. 126 indexed citations
6.
Navarro, Juan C. Acosta, Pablo Ortega, Javier García‐Serrano, et al.. (2019). December 2016: Linking the Lowest Arctic Sea-Ice Extent on Record with the Lowest European Precipitation Event on Record. Bulletin of the American Meteorological Society. 100(1). S43–S48. 13 indexed citations
7.
Roberts, Malcolm, Helene T. Hewitt, Adrian L. New, et al.. (2018). Coordinated global high resolution coupled climate modelling - PRIMAVERA. EGU General Assembly Conference Abstracts. 17903. 1 indexed citations
8.
Ménégoz, Martin, Roberto Bilbao, Omar Bellprat, Virginie Guémas, & Francisco J. Doblas‐Reyes. (2018). Forecasting the climate response to volcanic eruptions: prediction skill related to stratospheric aerosol forcing. Environmental Research Letters. 13(6). 64022–64022. 15 indexed citations
9.
Caron, Louis‐Philippe, Alasdair Hunter, Omar Bellprat, et al.. (2018). An R package for climate forecast verification. Environmental Modelling & Software. 103. 29–42. 32 indexed citations
10.
Day, Jonathan J., Steffen Tietsche, Matthew Collins, et al.. (2016). The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1. Geoscientific model development. 9(6). 2255–2270. 25 indexed citations
11.
Prodhomme, Chloé, Lauriane Batté, François Massonnet, et al.. (2016). Benefits of resolution increase for seasonal forecast quality in EC-Earth. EGUGA. 1 indexed citations
12.
García‐Serrano, Javier, Claude Frankignoul, Martin P. King, et al.. (2016). Multi-model assessment of linkages between eastern Arctic sea-ice variability and the Euro-Atlantic atmospheric circulation in current climate. Climate Dynamics. 49(7-8). 2407–2429. 25 indexed citations
13.
Guémas, Virginie, et al.. (2016). Decadal climate prediction with a refined anomaly initialisation approach. Climate Dynamics. 48(5-6). 1841–1853. 7 indexed citations
14.
Fučkar, Neven S., François Massonnet, Virginie Guémas, et al.. (2016). Record Low Northern Hemisphere Sea Ice Extent in March 2015. Bulletin of the American Meteorological Society. 97(12). S136–S140. 3 indexed citations
15.
Day, Jonathan J., Steffen Tietsche, Matthew Collins, et al.. (2015). The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set. Open Research Exeter (University of Exeter). 3 indexed citations
16.
Guémas, Virginie, Javier García‐Serrano, Annarita Mariotti, Francisco J. Doblas‐Reyes, & Louis‐Philippe Caron. (2014). Prospects for decadal climate prediction in the Mediterranean region. Quarterly Journal of the Royal Meteorological Society. 141(687). 580–597. 18 indexed citations
17.
Doblas‐Reyes, Francisco J., Yoshimitsu Chikamoto, Javier García‐Serrano, et al.. (2013). Initialized near-term regional climate change prediction. Nature Communications. 4(1). 1715–1715. 257 indexed citations
18.
Doblas‐Reyes, Francisco J., et al.. (2013). Dependence of the climate prediction skill on spatiotemporal scales: Internal versus radiatively‐forced contribution. Geophysical Research Letters. 40(12). 3213–3219. 4 indexed citations
19.
Guémas, Virginie & Francis Codron. (2011). Differing Impacts of Resolution Changes in Latitude and Longitude on the Midlatitudes in the LMDZ Atmospheric GCM. Journal of Climate. 24(22). 5831–5849. 18 indexed citations
20.

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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