Pierre Ailliot

1.5k total citations
44 papers, 812 citations indexed

About

Pierre Ailliot is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Pierre Ailliot has authored 44 papers receiving a total of 812 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Global and Planetary Change, 18 papers in Atmospheric Science and 14 papers in Oceanography. Recurrent topics in Pierre Ailliot's work include Climate variability and models (18 papers), Meteorological Phenomena and Simulations (13 papers) and Hydrology and Drought Analysis (10 papers). Pierre Ailliot is often cited by papers focused on Climate variability and models (18 papers), Meteorological Phenomena and Simulations (13 papers) and Hydrology and Drought Analysis (10 papers). Pierre Ailliot collaborates with scholars based in France, Argentina and United Kingdom. Pierre Ailliot's co-authors include Valérie Monbet, Marc Prevosto, Pierre Tandeo, C. Thompson, Peter C. Thomson, Ronan Fablet, Redouane Lguensat, Manuel Pulido Fernández, Robert B. Scott and Corwin J. Wright and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Geophysical Research Letters.

In The Last Decade

Pierre Ailliot

43 papers receiving 782 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre Ailliot France 15 316 307 181 154 140 44 812
Yongxiang Huang China 20 371 1.2× 252 0.8× 192 1.1× 288 1.9× 101 0.7× 75 1.2k
Thordis L. Thorarinsdottir Norway 18 926 2.9× 744 2.4× 41 0.2× 310 2.0× 178 1.3× 41 1.4k
David Randell United Kingdom 18 273 0.9× 167 0.5× 190 1.0× 178 1.2× 37 0.3× 49 761
William Kleiber United States 19 622 2.0× 439 1.4× 50 0.3× 531 3.4× 111 0.8× 57 1.5k
S. Adarsh India 22 769 2.4× 208 0.7× 49 0.3× 481 3.1× 146 1.0× 141 1.4k
Sebastian Lerch Germany 18 629 2.0× 712 2.3× 33 0.2× 346 2.2× 295 2.1× 45 1.2k
Michael Scheuerer United States 19 857 2.7× 875 2.9× 35 0.2× 266 1.7× 147 1.1× 39 1.3k
Stefano Castruccio United States 18 569 1.8× 329 1.1× 25 0.1× 344 2.2× 99 0.7× 55 1.1k
John Bjørnar Bremnes Norway 12 1.0k 3.3× 748 2.4× 40 0.2× 215 1.4× 348 2.5× 16 1.7k

Countries citing papers authored by Pierre Ailliot

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Ailliot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre Ailliot

This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Ailliot. A scholar is included among the top collaborators of Pierre Ailliot 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 Pierre Ailliot. Pierre Ailliot 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.
Sévellec, Florian, et al.. (2024). Selecting and weighting dynamical models using data-driven approaches. Nonlinear processes in geophysics. 31(3). 303–317. 1 indexed citations
2.
Ailliot, Pierre, et al.. (2024). EM algorithm for generalized Ridge regression with spatial covariates. Environmetrics. 35(6). 1 indexed citations
3.
Ailliot, Pierre, et al.. (2023). Statistical modeling of the space–time relation between wind and significant wave height. SHILAP Revista de lepidopterología. 9(1). 67–81. 1 indexed citations
4.
Tandeo, Pierre, Pierre Ailliot, & Florian Sévellec. (2023). Data-driven reconstruction of partially observed dynamical systems. Nonlinear processes in geophysics. 30(2). 129–137. 2 indexed citations
5.
Ailliot, Pierre, et al.. (2023). A meta-Gaussian distribution for sub-hourly rainfall. Stochastic Environmental Research and Risk Assessment. 37(10). 3915–3927. 2 indexed citations
6.
Legrand, J. F., et al.. (2023). Joint stochastic simulation of extreme coastal and offshore significant wave heights. The Annals of Applied Statistics. 17(4). 2 indexed citations
7.
Ruiz, Juan, Pierre Ailliot, Thi Tuyet Trang Chau, et al.. (2022). Analog data assimilation for the selection of suitable general circulation models. Geoscientific model development. 15(18). 7203–7220. 3 indexed citations
8.
Chau, Thi Tuyet Trang, et al.. (2022). Comparison of simulation-based algorithms for parameter estimation and state reconstruction in nonlinear state-space models. Discrete and Continuous Dynamical Systems - S. 16(2). 240–264. 4 indexed citations
9.
Yiou, Pascal, Philippe Naveau, Pierre Tandeo, et al.. (2021). Using Local Dynamics to Explain Analog Forecasting of Chaotic Systems. Journal of the Atmospheric Sciences. 78(7). 2117–2133. 13 indexed citations
10.
Tandeo, Pierre, et al.. (2018). Joint Estimation of Model and Observation Error Covariance Matrices in Data Assimilation: a Review. SPIRE - Sciences Po Institutional REpository. 9 indexed citations
11.
Lguensat, Redouane, Pierre Tandeo, Pierre Ailliot, Manuel Pulido Fernández, & Ronan Fablet. (2017). The Analog Data Assimilation. Monthly Weather Review. 145(10). 4093–4107. 94 indexed citations
12.
Lguensat, Redouane, Pierre Tandeo, Pierre Ailliot, Bertrand Chapron, & Ronan Fablet. (2016). Using archived datasets for missing data interpolation in ocean remote sensing observation series. OCEANS 2016 - Shanghai. 1–5. 4 indexed citations
13.
Prevosto, Marc, et al.. (2014). Modeling process asymmetries with Laplace moving average. Computational Statistics & Data Analysis. 81. 24–37. 1 indexed citations
14.
Bessac, Julie, Pierre Ailliot, & Valérie Monbet. (2014). Gaussian linear state‐space model for wind fields in the North‐East Atlantic. Environmetrics. 26(1). 29–38. 8 indexed citations
15.
Ailliot, Pierre, C. Thompson, & Peter C. Thomson. (2011). Mixed methods for fitting the GEV distribution. Water Resources Research. 47(5). 31 indexed citations
16.
Ailliot, Pierre & Valérie Monbet. (2011). Markov-switching autoregressive models for wind time series. Environmental Modelling & Software. 30. 92–101. 93 indexed citations
17.
Ailliot, Pierre. (2006). Some theoretical results on Markov-switching autoregressive models with gamma innovations. Comptes Rendus Mathématique. 343(4). 271–274. 4 indexed citations
18.
Ailliot, Pierre, et al.. (2005). An autoregressive model with time-varying coefficients for wind fields. Environmetrics. 17(2). 107–117. 53 indexed citations
19.
Ailliot, Pierre, et al.. (2003). Simulation of sea state parameters process to study the profitability of a maritime line. 5 indexed citations
20.
Ailliot, Pierre & Marc Prevosto. (2001). Two Methods For Simulating the Bivariate Process of Wave Height And Direction. 2 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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