Laure Raynaud

1.1k total citations
37 papers, 776 citations indexed

About

Laure Raynaud is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Laure Raynaud has authored 37 papers receiving a total of 776 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Atmospheric Science, 29 papers in Global and Planetary Change and 13 papers in Environmental Engineering. Recurrent topics in Laure Raynaud's work include Meteorological Phenomena and Simulations (28 papers), Climate variability and models (25 papers) and Wind and Air Flow Studies (12 papers). Laure Raynaud is often cited by papers focused on Meteorological Phenomena and Simulations (28 papers), Climate variability and models (25 papers) and Wind and Air Flow Studies (12 papers). Laure Raynaud collaborates with scholars based in France, United Kingdom and Réunion. Laure Raynaud's co-authors include François Bouttier, Olivier Nuissier, Loïk Berre, Gérald Desroziers, Benoît Vié, Massimo Bonavita, Jan Mewis, Benjamin Ménétrier, B. Ernst and Lars Isaksen and has published in prestigious journals such as Journal of Colloid and Interface Science, IEEE Transactions on Geoscience and Remote Sensing and Monthly Weather Review.

In The Last Decade

Laure Raynaud

36 papers receiving 747 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laure Raynaud France 14 630 612 179 54 43 37 776
T. S. V. Vijaya Kumar India 16 634 1.0× 573 0.9× 34 0.2× 12 0.2× 135 3.1× 51 929
Cathérine Meißner Germany 8 153 0.2× 158 0.3× 72 0.4× 18 0.3× 4 0.1× 12 367
Manoj K. Mishra India 13 110 0.2× 137 0.2× 55 0.3× 48 0.9× 56 1.3× 49 448
V. Gorshelev Germany 5 416 0.7× 290 0.5× 79 0.4× 7 0.1× 8 0.2× 5 482
Walter Debruyn Belgium 10 149 0.2× 38 0.1× 56 0.3× 29 0.5× 20 0.5× 35 384
R. A. Sutherland United States 12 217 0.3× 175 0.3× 113 0.6× 8 0.1× 7 0.2× 36 473
W. Chehade Germany 5 475 0.8× 349 0.6× 84 0.5× 6 0.1× 10 0.2× 6 534
R. Lesher United States 11 938 1.5× 305 0.5× 350 2.0× 14 0.3× 6 0.1× 13 1.1k
K.‐H. Wohlfrom Germany 9 421 0.7× 348 0.6× 31 0.2× 22 0.4× 15 0.3× 11 553
Eiichi Yoshikawa Japan 13 352 0.6× 117 0.2× 204 1.1× 13 0.2× 8 0.2× 62 536

Countries citing papers authored by Laure Raynaud

Since Specialization
Citations

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

Fields of papers citing papers by Laure Raynaud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laure Raynaud

This figure shows the co-authorship network connecting the top 25 collaborators of Laure Raynaud. A scholar is included among the top collaborators of Laure Raynaud 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 Laure Raynaud. Laure Raynaud 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.
Soler, Manuel, et al.. (2024). Pre‐tactical convection prediction for air traffic flow management using LSTM neural network. Meteorological Applications. 31(3). 1 indexed citations
2.
Raynaud, Laure, et al.. (2024). A Convolutional Neural Network for Tropical Cyclone Wind Structure Identification in Kilometer-Scale Forecasts. SPIRE - Sciences Po Institutional REpository. 3(2). 3 indexed citations
3.
Brun, François, et al.. (2024). Assessing the impact of weather forecast uncertainties in crop water stress model predictions. Agricultural and Forest Meteorology. 349. 109934–109934. 1 indexed citations
4.
Plu, Matthieu, Laure Raynaud, & Pierre Brousseau. (2024). La prévision d'ensemble au coeur de la prévision numérique du temps : état des lieux et perspectives. La Météorologie. 36–36.
5.
Raynaud, Laure, et al.. (2023). Multivariate Emulation of Kilometer-Scale Numerical Weather Predictions with Generative Adversarial Networks: A Proof of Concept. SPIRE - Sciences Po Institutional REpository. 2(4). 1 indexed citations
6.
Korsakissok, Irène, et al.. (2022). Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a 85 Kr field campaign. Atmospheric chemistry and physics. 22(24). 15793–15816. 5 indexed citations
7.
Raynaud, Laure, et al.. (2021). Design and Evaluation of Calibrated and Seamless Ensemble Weather Forecasts for Crop Protection Applications. Weather and Forecasting. 36(4). 1329–1342. 2 indexed citations
8.
Raynaud, Laure, et al.. (2021). Sensitivity analysis of the convective‐scale AROME model to physical and dynamical parameters. Quarterly Journal of the Royal Meteorological Society. 148(743). 920–942. 4 indexed citations
9.
Keil, Christian, et al.. (2020). Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control. Atmospheric chemistry and physics. 20(24). 15851–15865. 9 indexed citations
10.
11.
Arbogast, Philippe, et al.. (2019). The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts. Advances in science and research. 16. 209–213. 3 indexed citations
12.
Bouttier, François & Laure Raynaud. (2018). Clustering and selection of boundary conditions for limited‐area ensemble prediction. Quarterly Journal of the Royal Meteorological Society. 144(717). 2381–2391. 14 indexed citations
13.
Arbogast, Philippe, et al.. (2016). Object‐oriented processing of CRM precipitation forecasts by stochastic filtering. Quarterly Journal of the Royal Meteorological Society. 142(700). 2827–2838. 9 indexed citations
14.
Bouttier, François, Laure Raynaud, Olivier Nuissier, & Benjamin Ménétrier. (2015). Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX. Quarterly Journal of the Royal Meteorological Society. 142(S1). 390–403. 69 indexed citations
15.
Raynaud, Laure, Olivier Pannekoucke, Philippe Arbogast, & François Bouttier. (2014). Application of a Bayesian weighting for short‐range lagged ensemble forecasting at the convective scale. Quarterly Journal of the Royal Meteorological Society. 141(687). 459–468. 10 indexed citations
16.
Raynaud, Laure & Olivier Pannekoucke. (2012). Sampling properties and spatial filtering of ensemble background‐error length‐scales. Quarterly Journal of the Royal Meteorological Society. 139(672). 784–794. 8 indexed citations
17.
Raynaud, Laure & Olivier Pannekoucke. (2012). Heterogeneous filtering of ensemble‐based background‐error variances. Quarterly Journal of the Royal Meteorological Society. 138(667). 1589–1598. 4 indexed citations
18.
Raynaud, Laure, Loïk Berre, & Gérald Desroziers. (2011). An extended specification of flow‐dependent background error variances in the Météo‐France global 4D‐Var system. Quarterly Journal of the Royal Meteorological Society. 137(656). 607–619. 38 indexed citations
19.
Raynaud, Laure, Loïk Berre, & Gérald Desroziers. (2009). Objective filtering of ensemble‐based background‐error variances. Quarterly Journal of the Royal Meteorological Society. 135(642). 1177–1199. 51 indexed citations
20.
Raynaud, Laure. (1999). Improved modelling of propagation and backscattering of millimetre waves in the melting layer. 1999. 160–163. 1 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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