Maëlle Nodet

1.5k total citations
21 papers, 718 citations indexed

About

Maëlle Nodet is a scholar working on Atmospheric Science, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics. According to data from OpenAlex, Maëlle Nodet has authored 21 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Atmospheric Science, 6 papers in Statistics, Probability and Uncertainty and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in Maëlle Nodet's work include Meteorological Phenomena and Simulations (8 papers), Probabilistic and Robust Engineering Design (6 papers) and Cryospheric studies and observations (5 papers). Maëlle Nodet is often cited by papers focused on Meteorological Phenomena and Simulations (8 papers), Probabilistic and Robust Engineering Design (6 papers) and Cryospheric studies and observations (5 papers). Maëlle Nodet collaborates with scholars based in France, United States and Ukraine. Maëlle Nodet's co-authors include Mark Asch, Marc Bocquet, Clémentine Prieur, Alexandre Janon, Thierry Klein, Agnès Lagnoux, Catherine Ritz, Thomas Zwinger, Fabien Gillet‐Chaulet and Olivier Gagliardini and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Tellus A Dynamic Meteorology and Oceanography.

In The Last Decade

Maëlle Nodet

20 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maëlle Nodet France 10 396 157 139 102 90 21 718
Christian Allen United Kingdom 16 175 0.4× 25 0.2× 27 0.2× 47 0.5× 103 1.1× 73 1.3k
Ed Bueler United States 18 1.5k 3.8× 13 0.1× 145 1.0× 522 5.1× 463 5.1× 31 1.9k
Gardar Johannesson United States 10 205 0.5× 49 0.3× 310 2.2× 3 0.0× 7 0.1× 19 1.1k
Stefano Ubbiali Switzerland 3 137 0.3× 129 0.8× 121 0.9× 5 0.0× 3 0.0× 5 539
Christopher E. Kees United States 19 41 0.1× 19 0.1× 29 0.2× 15 0.1× 17 0.2× 64 1.2k
Alberto Carrassi France 22 1.2k 3.1× 27 0.2× 976 7.0× 4 0.0× 18 0.2× 73 1.7k
A. McD. Mercer Canada 14 70 0.2× 31 0.2× 40 0.3× 6 0.1× 6 0.1× 55 632
Maria Rightley United States 4 54 0.1× 264 1.7× 43 0.3× 3 0.0× 5 0.1× 8 640
S. I. Aanonsen Norway 23 142 0.4× 32 0.2× 115 0.8× 2 0.0× 7 0.1× 65 2.5k
Hansjörg Kutterer Germany 14 95 0.2× 54 0.3× 68 0.5× 3 0.0× 12 0.1× 75 802

Countries citing papers authored by Maëlle Nodet

Since Specialization
Citations

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

Fields of papers citing papers by Maëlle Nodet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maëlle Nodet

This figure shows the co-authorship network connecting the top 25 collaborators of Maëlle Nodet. A scholar is included among the top collaborators of Maëlle Nodet 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 Maëlle Nodet. Maëlle Nodet 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.
Chabot, Vincent, Maëlle Nodet, & Arthur Vidard. (2020). Multiscale Representation of Observation Error Statistics in Data Assimilation. Sensors. 20(5). 1460–1460. 3 indexed citations
2.
Vidard, Arthur, et al.. (2018). Optimal transport for variational data assimilation. Nonlinear processes in geophysics. 25(1). 55–66. 9 indexed citations
3.
Janon, Alexandre, Maëlle Nodet, Christophe Prieur, & Clémentine Prieur. (2018). Goal-oriented error estimation for parameter-dependent nonlinear problems. ESAIM Mathematical Modelling and Numerical Analysis. 52(2). 705–728. 1 indexed citations
4.
Janon, Alexandre, Maëlle Nodet, Christophe Prieur, & Clémentine Prieur. (2016). Goal-oriented error estimation for fast approximations of nonlinear problems. 1 indexed citations
5.
Asch, Mark, Marc Bocquet, & Maëlle Nodet. (2016). Data Assimilation. Society for Industrial and Applied Mathematics eBooks. 199 indexed citations
6.
Chabot, Vincent, Maëlle Nodet, Nicolas Papadakis, & Arthur Vidard. (2015). Accounting for observation errors in image data assimilation. Tellus A Dynamic Meteorology and Oceanography. 67(1). 23629–23629. 9 indexed citations
7.
Janon, Alexandre, Maëlle Nodet, & Clémentine Prieur. (2015). Goal-Oriented Error Estimation for the Reduced Basis Method, with Application to Sensitivity Analysis. Journal of Scientific Computing. 68(1). 21–41. 5 indexed citations
8.
Bonan, Bertrand, Maëlle Nodet, Catherine Ritz, & Vincent Peyaud. (2014). An ETKF approach for initial state and parameter estimation in ice sheet modelling. Nonlinear processes in geophysics. 21(2). 569–582. 11 indexed citations
9.
Janon, Alexandre, Thierry Klein, Agnès Lagnoux, Maëlle Nodet, & Clémentine Prieur. (2013). Asymptotic normality and efficiency of two Sobol index estimators. ESAIM Probability and Statistics. 18. 342–364. 151 indexed citations
10.
Gillet‐Chaulet, Fabien, Olivier Gagliardini, Hakime Seddik, et al.. (2012). Greenland ice sheet contribution to sea-level rise from a new-generation ice-sheet model. ˜The œcryosphere. 6(6). 1561–1576. 184 indexed citations
11.
Janon, Alexandre, Maëlle Nodet, & Clémentine Prieur. (2012). UNCERTAINTIES ASSESSMENT IN GLOBAL SENSITIVITY INDICES ESTIMATION FROM METAMODELS. International Journal for Uncertainty Quantification. 4(1). 21–36. 27 indexed citations
12.
Janon, Alexandre, Maëlle Nodet, & Clémentine Prieur. (2012). Certified reduced-basis solutions of viscous Burgers equation parametrized by initial and boundary values. ESAIM Mathematical Modelling and Numerical Analysis. 47(2). 317–348. 10 indexed citations
13.
Janon, Alexandre, Maëlle Nodet, & Clémentine Prieur. (2012). Certified metamodels for sensitivity indices estimation. SHILAP Revista de lepidopterología. 35. 234–238. 2 indexed citations
14.
Nodet, Maëlle, et al.. (2011). Investigating changes in basal conditions of Variegated Glacier prior to and during its 1982–1983 surge. ˜The œcryosphere. 5(3). 659–672. 56 indexed citations
15.
Gillet‐Chaulet, Fabien, Olivier Gagliardini, Maëlle Nodet, et al.. (2011). Investigating Greenland Ice Sheet dynamics over next century using high resolution full-Stokes simulations. AGUFM. 2011. 1 indexed citations
16.
Auroux, Didier, Jacques Blum, & Maëlle Nodet. (2011). Diffusive Back and Forth Nudging algorithm for data assimilation. Comptes Rendus Mathématique. 349(15-16). 849–854. 10 indexed citations
17.
Gillet‐Chaulet, Fabien, Olivier Gagliardini, Maëlle Nodet, et al.. (2011). Full-Stokes finite element modelling of the Greenland ice-sheet using inverse methods.. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
18.
Lebeau, Gilles & Maëlle Nodet. (2010). Experimental Study of the HUM Control Operator for Linear Waves. Experimental Mathematics. 19(1). 93–120. 13 indexed citations
19.
Nodet, Maëlle. (2009). Optimal control of the Primitive Equations of the ocean with Lagrangian observations. ESAIM Control Optimisation and Calculus of Variations. 16(2). 400–419.
20.
Nodet, Maëlle. (2006). Variational assimilation of Lagrangian data in oceanography. Inverse Problems. 22(1). 245–263. 4 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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