Patrick Laloyaux

31.4k total citations · 1 hit paper
16 papers, 1.6k citations indexed

About

Patrick Laloyaux is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Patrick Laloyaux has authored 16 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Atmospheric Science, 14 papers in Global and Planetary Change and 4 papers in Oceanography. Recurrent topics in Patrick Laloyaux's work include Meteorological Phenomena and Simulations (16 papers), Climate variability and models (14 papers) and Oceanographic and Atmospheric Processes (3 papers). Patrick Laloyaux is often cited by papers focused on Meteorological Phenomena and Simulations (16 papers), Climate variability and models (14 papers) and Oceanographic and Atmospheric Processes (3 papers). Patrick Laloyaux collaborates with scholars based in United Kingdom, France and United States. Patrick Laloyaux's co-authors include Massimo Bonavita, Dick Dee, Hans Hersbach, Paul Poli, Jean‐Noël Thépaut, Magdalena Balmaseda, Elías Hólm, Carole Peubey, David G. H. Tan and Frédéric Vitart and has published in prestigious journals such as Journal of Climate, Monthly Weather Review and Quarterly Journal of the Royal Meteorological Society.

In The Last Decade

Patrick Laloyaux

16 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

ERA-20C: An Atmospheric Reanalysis of the Twentieth Century

2016 839 citations Paul Poli, Hans Hersbach et al. Journal of Climate profile →

Peers

Patrick Laloyaux

GPC

OCEAN

WST

Massimo Bonavita United Kingdom

Daniel Klocke Germany

Steffen Tietsche United Kingdom

Susanna Corti Italy

Lucas Harris United States

Elías Hólm United Kingdom

Baijun Tian United States

Mu Mu China

Catherine Rio France

Florent Brient France

Massimo Bonavita United Kingdom

Patrick Laloyaux

1.7k ×1.3

GPC

1.8k ×1.4

466 ×0.9

OCEAN

214 ×2.2

62 ×0.9

WST

Citations per year, relative to Patrick Laloyaux Patrick Laloyaux (= 1×) peers Massimo Bonavita

Countries citing papers authored by Patrick Laloyaux

Since Specialization

Citations

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

Fields of papers citing papers by Patrick Laloyaux

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Laloyaux

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

All Works

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16 of 16 papers shown

Farchi, Alban, Marcin Chrust, Marc Bocquet, Patrick Laloyaux, & Massimo Bonavita. (2023). Online Model Error Correction With Neural Networks in the Incremental 4D‐Var Framework. Journal of Advances in Modeling Earth Systems. 15(9). 14 indexed citations

Laloyaux, Patrick, Thorsten Kurth, Peter Dueben, & David Hall. (2022). Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System. Journal of Advances in Modeling Earth Systems. 14(6). 20 indexed citations

Farchi, Alban, Patrick Laloyaux, Massimo Bonavita, & Marc Bocquet. (2021). Using machine learning to correct model error in data assimilation and forecast applications. Quarterly Journal of the Royal Meteorological Society. 147(739). 3067–3084. 77 indexed citations

Farchi, Alban, Patrick Laloyaux, Massimo Bonavita, & Marc Bocquet. (2021). Using machine learning to correct model error in data assimilation and forecast applications. 4 indexed citations

Bonavita, Massimo & Patrick Laloyaux. (2020). Machine Learning for Model Error Inference and Correction. Journal of Advances in Modeling Earth Systems. 12(12). 91 indexed citations

Laloyaux, Patrick, Massimo Bonavita, Mohamed Dahoui, et al.. (2020). Towards an unbiased stratospheric analysis. Quarterly Journal of the Royal Meteorological Society. 146(730). 2392–2409. 24 indexed citations

Laloyaux, Patrick, Massimo Bonavita, Marcin Chrust, & Selime Gürol. (2020). Exploring the potential and limitations of weak‐constraint 4D‐Var. Quarterly Journal of the Royal Meteorological Society. 146(733). 4067–4082. 15 indexed citations

Laloyaux, Patrick, Eric de Boisséson, Magdalena Balmaseda, et al.. (2018). CERA‐20C: A Coupled Reanalysis of the Twentieth Century. Journal of Advances in Modeling Earth Systems. 10(5). 1172–1195. 214 indexed citations

Laloyaux, Patrick, Sergey Frolov, Benjamin Ménétrier, & Massimo Bonavita. (2018). Implicit and explicit cross‐correlations in coupled data assimilation. Quarterly Journal of the Royal Meteorological Society. 144(715). 1851–1863. 17 indexed citations

10.

Poli, Paul, Hans Hersbach, Dick Dee, et al.. (2016). ERA-20C: An Atmospheric Reanalysis of the Twentieth Century. Journal of Climate. 29(11). 4083–4097. 839 indexed citations breakdown →

11.

Laloyaux, Patrick, Jean‐Noël Thépaut, & Dick Dee. (2016). Impact of Scatterometer Surface Wind Data in the ECMWF Coupled Assimilation System. Monthly Weather Review. 144(3). 1203–1217. 30 indexed citations

12.

Laloyaux, Patrick, Magdalena Balmaseda, Dick Dee, Kristian Mogensen, & Peter A. E. M. Janssen. (2015). A coupled data assimilation system for climate reanalysis. Quarterly Journal of the Royal Meteorological Society. 142(694). 65–78. 159 indexed citations

13.

Mulholland, David P., Patrick Laloyaux, Keith Haines, & Magdalena Balmaseda. (2015). Origin and Impact of Initialization Shocks in Coupled Atmosphere–Ocean Forecasts*. Monthly Weather Review. 143(11). 4631–4644. 71 indexed citations

14.

Brassington, Gary B., Matthew Martin, Hendrik L. Tolman, et al.. (2015). Progress and challenges in short- to medium-range coupled prediction. Journal of Operational Oceanography. 8(sup2). s239–s258. 34 indexed citations

15.

Gratton, Serge, et al.. (2013). Derivative‐free optimization for large‐scale nonlinear data assimilation problems. Quarterly Journal of the Royal Meteorological Society. 140(680). 943–957. 4 indexed citations

16.

Gratton, Serge, et al.. (2011). A reduced and limited‐memory preconditioned approach for the 4D‐Var data‐assimilation problem. Quarterly Journal of the Royal Meteorological Society. 137(655). 452–466. 5 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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