Nina Raoult

755 total citations
22 papers, 386 citations indexed

About

Nina Raoult is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Nina Raoult has authored 22 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Global and Planetary Change, 12 papers in Atmospheric Science and 4 papers in Environmental Engineering. Recurrent topics in Nina Raoult's work include Climate variability and models (11 papers), Plant Water Relations and Carbon Dynamics (10 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Nina Raoult is often cited by papers focused on Climate variability and models (11 papers), Plant Water Relations and Carbon Dynamics (10 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Nina Raoult collaborates with scholars based in France, United Kingdom and United States. Nina Raoult's co-authors include Peter M. Cox, Tim E. Jupp, Catherine M. Luke, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, Natasha MacBean, Benjamin N. Sulman, Russell L. Scott and Jeffrey D. Wood and has published in prestigious journals such as Nature Communications, Global Change Biology and Nature Geoscience.

In The Last Decade

Nina Raoult

21 papers receiving 381 citations

Peers

Nina Raoult

GPC

ECOLO

Yam Prasad Dhital China

Ji Qi United States

Yonge Zhang China

Ernst Leitgeb Austria

Andrew Zumkehr United States

Gregor Feig South Africa

S. K. Kaharabata Canada

Yuli Liu China

Shanqian Wang China

Yam Prasad Dhital China

Nina Raoult

140 ×0.6

GPC

89 ×0.6

89 ×1.2

65 ×0.9

54 ×1.1

ECOLO

Citations per year, relative to Nina Raoult Nina Raoult (= 1×) peers Yam Prasad Dhital

Countries citing papers authored by Nina Raoult

Since Specialization

Citations

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

Fields of papers citing papers by Nina Raoult

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Raoult

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Raoult. A scholar is included among the top collaborators of Nina Raoult 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 Nina Raoult. Nina Raoult is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Raoult, Nina, James M. Salter, F. Hourdin, et al.. (2024). Exploring the potential of history matching for land surface model calibration. Geoscientific model development. 17(15). 5779–5801. 2 indexed citations

Charbit, Sylvie, Christophe Dumas, Fabienne Maignan, et al.. (2024). Modelling snowpack on ice surfaces with the ORCHIDEE land surface model: application to the Greenland ice sheet. The cryosphere. 18(11). 5067–5099. 1 indexed citations

Raoult, Nina, Nicolas Vuichard, Vladislav Bastrikov, et al.. (2024). Using Free Air CO ₂ Enrichment data to constrain land surface model projections of the terrestrial carbon cycle. Biogeosciences. 21(4). 1017–1036. 1 indexed citations

Cox, Peter M., Mark S. Williamson, Pierre Friedlingstein, et al.. (2024). Emergent constraints on carbon budgets as a function of global warming. Nature Communications. 15(1). 1885–1885. 14 indexed citations

Mercado, Lina M., et al.. (2024). Night-time decline in plant respiration is consistent with substrate depletion. Communications Earth & Environment. 5(1). 10 indexed citations

Raoult, Nina, Sylvie Charbit, Christophe Dumas, et al.. (2023). Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals. The cryosphere. 17(7). 2705–2724. 4 indexed citations

Raoult, Nina, Tim E. Jupp, Ben Booth, & Peter M. Cox. (2023). Combining local model calibration with the emergent constraint approach to reduce uncertainty in the tropical land carbon cycle feedback. Earth System Dynamics. 14(4). 723–731. 3 indexed citations

Yin, Zun, Kirsten L. Findell, Paul A. Dirmeyer, et al.. (2023). Daytime-only mean data enhance understanding of land–atmosphere coupling. Hydrology and earth system sciences. 27(4). 861–872. 7 indexed citations

Maignan, Fabienne, Marine Remaud, Wu Sun, et al.. (2023). Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations. Journal of Geophysical Research Biogeosciences. 128(7). 4 indexed citations

10.

Maignan, Fabienne, Marine Remaud, Jérôme Ogée, et al.. (2022). Global modelling of soil carbonyl sulfide exchanges. Biogeosciences. 19(9). 2427–2463. 15 indexed citations

11.

Novick, Kimberly A., Darren L. Ficklin, Dennis Baldocchi, et al.. (2022). Confronting the water potential information gap. Nature Geoscience. 15(3). 158–164. 95 indexed citations

12.

Raoult, Nina, et al.. (2022). Soil Moisture Drydown Detection Is Hindered by Model-Based Rescaling. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 3 indexed citations

13.

Kwon, Min Jung, Ashley P. Ballantyne, Philippe Ciais, et al.. (2022). Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands. Global Change Biology. 28(22). 6752–6770. 25 indexed citations

14.

Maignan, Fabienne, Marine Remaud, Jérôme Ogée, et al.. (2021). Global modelling of soil carbonyl sulfide exchange. 1 indexed citations

15.

Maignan, Fabienne, Marine Remaud, Linda M. J. Kooijmans, et al.. (2021). Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach. Biogeosciences. 18(9). 2917–2955. 28 indexed citations

16.

Ottlé, Catherine, et al.. (2021). Variance Based Sensitivity Analysis of FLake Lake Model for Global Land Surface Modeling. Journal of Geophysical Research Atmospheres. 126(8). 7 indexed citations

17.

Raoult, Nina, et al.. (2018). Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation. Remote Sensing. 10(11). 1786–1786. 22 indexed citations

18.

Raoult, Nina, Tim E. Jupp, Peter M. Cox, & Catherine M. Luke. (2016). Land surface parameter optimisation through data assimilation: the adJULES system.

19.

Raoult, Nina, Tim E. Jupp, Peter M. Cox, & Catherine M. Luke. (2016). Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0. Geoscientific model development. 9(8). 2833–2852. 47 indexed citations

20.

Ouvrard, Stéphanie, Pascale Bauda, Thierry Béguiristain, et al.. (2011). In Situ Assessment of Phytotechnologies for Multicontaminated Soil Management. International Journal of Phytoremediation. 13(sup1). 245–263. 63 indexed citations

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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