Matthew Simpson

578 total citations
30 papers, 365 citations indexed

About

Matthew Simpson is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Matthew Simpson has authored 30 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Global and Planetary Change, 18 papers in Atmospheric Science and 11 papers in Environmental Engineering. Recurrent topics in Matthew Simpson's work include Meteorological Phenomena and Simulations (15 papers), Wind and Air Flow Studies (8 papers) and Climate variability and models (6 papers). Matthew Simpson is often cited by papers focused on Meteorological Phenomena and Simulations (15 papers), Wind and Air Flow Studies (8 papers) and Climate variability and models (6 papers). Matthew Simpson collaborates with scholars based in United States, India and Australia. Matthew Simpson's co-authors include Sethu Raman, R. SURESH, U. C. Mohanty, D. D. Lucas, Hari Warrior, Charles R. Carrigan, G Sugiyama, Yunwei Sun, S. Raman and John S. Nasstrom and has published in prestigious journals such as Journal of the American Statistical Association, Scientific Reports and Geophysical Research Letters.

In The Last Decade

Matthew Simpson

28 papers receiving 353 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Simpson United States 12 197 175 116 33 28 30 365
R. H. Maryon United Kingdom 12 324 1.6× 323 1.8× 151 1.3× 41 1.2× 18 0.6× 21 503
Réal D’Amours Canada 17 493 2.5× 278 1.6× 141 1.2× 272 8.2× 31 1.1× 24 732
D. B. Ryall United Kingdom 13 662 3.4× 724 4.1× 108 0.9× 8 0.2× 78 2.8× 21 976
W. Klug Germany 8 197 1.0× 214 1.2× 241 2.1× 24 0.7× 2 0.1× 16 391
Andrew Clark Australia 9 142 0.7× 147 0.8× 65 0.6× 4 0.1× 7 0.3× 16 462
Jordan R. Bell United States 10 297 1.5× 166 0.9× 88 0.8× 3 0.1× 3 0.1× 39 464
A. J. Janssen Netherlands 6 89 0.5× 144 0.8× 29 0.3× 2 0.1× 3 0.1× 8 344
Ioanna Ioannou United Kingdom 15 53 0.3× 103 0.6× 48 0.4× 6 0.2× 38 666
G Loosmore United States 6 178 0.9× 171 1.0× 106 0.9× 21 0.6× 8 378
Antti Mäkelä Finland 14 379 1.9× 238 1.4× 57 0.5× 6 0.2× 50 578

Countries citing papers authored by Matthew Simpson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Simpson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Simpson

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Simpson. A scholar is included among the top collaborators of Matthew Simpson 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 Matthew Simpson. Matthew Simpson 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.
Monache, Luca Delle, Vesta Afzali Gorooh, Daniel F. Steinhoff, et al.. (2024). Deep Learning of a 200-Member Ensemble with a Limited Historical Training to Improve the Prediction of Extreme Precipitation Events. Monthly Weather Review. 152(7). 1587–1605. 5 indexed citations
2.
Oakley, Nina S., Tao Liu, Luke A. McGuire, et al.. (2023). Toward Probabilistic Post-Fire Debris-Flow Hazard Decision Support. Bulletin of the American Meteorological Society. 104(9). E1587–E1605. 16 indexed citations
3.
Simpson, Matthew, et al.. (2022). An Overview of Univariate and Multivariate Karhunen Loève Expansions in Statistics. 23(2). 285–326. 5 indexed citations
4.
Pallotta, Giuliana, et al.. (2021). Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models. Atmosphere. 12(8). 953–953. 10 indexed citations
5.
Kirstetter, Pierre‐Emmanuel, et al.. (2020). Probabilistic Quantitative Precipitation Estimation. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
6.
Carrigan, Charles R., et al.. (2020). Gas transport across the low-permeability containment zone of an underground nuclear explosion. Scientific Reports. 10(1). 1437–1437. 9 indexed citations
7.
Sansó, Bruno, et al.. (2019). Inferring Atmospheric Release Characteristics in a Large Computer Experiment Using Bayesian Adaptive Splines. Journal of the American Statistical Association. 114(528). 1450–1465. 21 indexed citations
8.
Lucas, D. D., Giuliana Pallotta, & Matthew Simpson. (2018). Using Machine Learning to Intelligently Select Members of Large Atmospheric Model Ensembles. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
9.
Carrigan, Charles R., Yunwei Sun, & Matthew Simpson. (2018). The characteristic release of noble gases from an underground nuclear explosion. Journal of Environmental Radioactivity. 196. 91–97. 16 indexed citations
10.
Mirocha, Jeffrey D., et al.. (2015). Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model. Wind Energy. 19(4). 739–762. 15 indexed citations
11.
Wharton, Sonia, Matthew Simpson, J. L. Osuna, Jennifer F. Newman, & Sébastien Biraud. (2014). Role of Surface Energy Exchange for Simulating Wind Turbine Inflow: A Case Study in the Southern Great Plains, USA. Atmosphere. 6(1). 21–49. 11 indexed citations
12.
Edmunds, Thomas, et al.. (2014). Integrated stochastic weather and production simulation modeling. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 128. 1–5. 2 indexed citations
13.
Sugiyama, G, et al.. (2012). NARAC Modeling During the Response to the Fukushima Dai-ichi Nuclear Power Plant Emergency. University of North Texas Digital Library (University of North Texas). 4 indexed citations
14.
Sugiyama, G, et al.. (2012). National Atmospheric Release Advisory Center Dispersion Modeling During the Fukushima Daiichi Nuclear Power Plant Accident. University of North Texas Digital Library (University of North Texas). 4 indexed citations
15.
Sugiyama, G, et al.. (2010). National Atmospheric Release Advisory Center (NARAC) Capabilities for Homeland Security. University of North Texas Digital Library (University of North Texas). 3 indexed citations
16.
Gloster, J., Andrew Jones, Alison L. Redington, et al.. (2009). Airborne spread of foot-and-mouth disease – Model intercomparison. The Veterinary Journal. 183(3). 278–286. 45 indexed citations
17.
Monache, Luca Delle, et al.. (2009). A new urban boundary layer and dispersion parameterization for an emergency response modeling system: Tests with the Joint Urban 2003 data set. Atmospheric Environment. 43(36). 5807–5821. 10 indexed citations
18.
Simpson, Matthew & S. Raman. (2006). Observations and numerical simulation of the sea and land breeze circulations along the west coast of India. 5 indexed citations
19.
Simpson, Matthew. (2006). Role of Urban Land Use on Mesoscale Circulations and Precipitation. NCSU Libraries Repository (North Carolina State University Libraries). 2 indexed citations
20.
Raman, Sethu, Dev Niyogi, Matthew Simpson, & Jacques Pelon. (2002). Dynamics of the elevated land plume over the Arabian Sea and the Northern Indian Ocean during northeasterly monsoons and during the Indian Ocean experiment (INDOEX). Geophysical Research Letters. 29(16). 13 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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