Philip G. Sansom

784 total citations
18 papers, 519 citations indexed

About

Philip G. Sansom is a scholar working on Global and Planetary Change, Atmospheric Science and Ophthalmology. According to data from OpenAlex, Philip G. Sansom has authored 18 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Global and Planetary Change, 9 papers in Atmospheric Science and 3 papers in Ophthalmology. Recurrent topics in Philip G. Sansom's work include Climate variability and models (11 papers), Meteorological Phenomena and Simulations (8 papers) and Atmospheric and Environmental Gas Dynamics (5 papers). Philip G. Sansom is often cited by papers focused on Climate variability and models (11 papers), Meteorological Phenomena and Simulations (8 papers) and Atmospheric and Environmental Gas Dynamics (5 papers). Philip G. Sansom collaborates with scholars based in United Kingdom, United States and France. Philip G. Sansom's co-authors include David B. Stephenson, Giuseppe Zappa, Len Shaffrey, Kevin I. Hodges, Christopher A. T. Ferro, Penelope Maher, John Methven, Geoffrey K. Vallis, Mark J. Webb and Steven C. Sherwood and has published in prestigious journals such as Journal of the American Statistical Association, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Philip G. Sansom

17 papers receiving 510 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip G. Sansom United Kingdom 9 418 368 60 37 34 18 519
Linyin Cheng United States 9 359 0.9× 259 0.7× 57 0.9× 52 1.4× 32 0.9× 18 567
Lívia Márcia Mosso Dutra Brazil 12 419 1.0× 300 0.8× 79 1.3× 117 3.2× 66 1.9× 26 599
Michael Hantel Austria 13 405 1.0× 537 1.5× 55 0.9× 72 1.9× 22 0.6× 53 701
Sylvie Jourdain France 10 463 1.1× 433 1.2× 43 0.7× 34 0.9× 21 0.6× 18 582
Ajay Raghavendra United States 13 445 1.1× 307 0.8× 70 1.2× 34 0.9× 51 1.5× 24 552
Alberto Mavume Mozambique 9 292 0.7× 309 0.8× 177 3.0× 19 0.5× 35 1.0× 15 480
Pankaj Bhardwaj India 13 258 0.6× 174 0.5× 84 1.4× 48 1.3× 27 0.8× 25 360
Tao Geng China 15 507 1.2× 376 1.0× 292 4.9× 27 0.7× 46 1.4× 30 677
C. Dunning United Kingdom 7 456 1.1× 349 0.9× 67 1.1× 38 1.0× 38 1.1× 8 582
Liesl L. Dyson South Africa 11 300 0.7× 240 0.7× 32 0.5× 16 0.4× 20 0.6× 22 420

Countries citing papers authored by Philip G. Sansom

Since Specialization
Citations

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

Fields of papers citing papers by Philip G. Sansom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip G. Sansom. 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 Philip G. Sansom. The network helps show where Philip G. Sansom may publish in the future.

Co-authorship network of co-authors of Philip G. Sansom

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

All Works

18 of 18 papers shown
1.
Sansom, Philip G. & Jennifer L. Catto. (2024). Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5. Geoscientific model development. 17(16). 6137–6151. 2 indexed citations
2.
Manning, Colin, Elizabeth Kendon, Hayley J. Fowler, et al.. (2024). Compound wind and rainfall extremes: Drivers and future changes over the UK and Ireland. Weather and Climate Extremes. 44. 100673–100673. 10 indexed citations
3.
Sansom, Philip G., et al.. (2022). Breed distribution of spontaneous chronic corneal epithelial defects in UK dogs. Veterinary Record. 192(5). e2031–e2031. 2 indexed citations
4.
5.
Sansom, Philip G., et al.. (2021). Magnetic resonance imaging of the normal canine eye using a T1‐weighted volumetric acquisition. Veterinary Record. 189(8). e505–e505.
6.
Sansom, Philip G., David B. Stephenson, & Thomas J. Bracegirdle. (2020). On Constraining Projections of Future Climate Using Observations and Simulations From Multiple Climate Models. Journal of the American Statistical Association. 116(534). 546–557. 6 indexed citations
7.
Sansom, Philip G., et al.. (2020). The prevalence of uveitis in a population of donkeys in the UK. Equine Veterinary Journal. 52(6). 863–867. 4 indexed citations
8.
Sansom, Philip G., et al.. (2019). Prevalence of antibody seroconversion to Toxoplasma gondii in uveitis and non‐uveitis dogs. Veterinary Record Open. 6(1). e000318–e000318. 3 indexed citations
9.
Maher, Penelope, et al.. (2019). Is the subtropical jet shifting poleward?. Climate Dynamics. 54(3-4). 1741–1759. 34 indexed citations
10.
Sansom, Philip G., Daniel Williamson, & David B. Stephenson. (2019). State Space Models for Non-Stationary Intermittently Coupled Systems: An Application to the North Atlantic Oscillation. Journal of the Royal Statistical Society Series C (Applied Statistics). 68(5). 1259–1280. 1 indexed citations
11.
Maher, Penelope, Geoffrey K. Vallis, Steven C. Sherwood, Mark J. Webb, & Philip G. Sansom. (2018). The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models. Geophysical Research Letters. 45(8). 3728–3736. 29 indexed citations
12.
Sansom, Philip G., Christopher A. T. Ferro, David B. Stephenson, Lisa Goddard, & Simon J. Mason. (2016). Best Practices for Postprocessing Ensemble Climate Forecasts. Part I: Selecting Appropriate Recalibration Methods. Journal of Climate. 29(20). 7247–7264. 25 indexed citations
13.
Hewitt, Alan J., Ben Booth, Chris Jones, et al.. (2016). Sources of Uncertainty in Future Projections of the Carbon Cycle. Journal of Climate. 29(20). 7203–7213. 21 indexed citations
14.
Siegert, Stefan, Philip G. Sansom, & Robin M. Williams. (2015). Parameter uncertainty in forecast recalibration. Quarterly Journal of the Royal Meteorological Society. 142(696). 1213–1221. 9 indexed citations
15.
Sansom, Philip G., et al.. (2013). A case‐association cluster detection and visualisation tool with an application to Legionnaires’ disease. Statistics in Medicine. 32(20). 3522–3538. 6 indexed citations
16.
Sansom, Philip G., David B. Stephenson, Christopher A. T. Ferro, Giuseppe Zappa, & Len Shaffrey. (2013). Simple Uncertainty Frameworks for Selecting Weighting Schemes and Interpreting Multimodel Ensemble Climate Change Experiments. Journal of Climate. 26(12). 4017–4037. 58 indexed citations
17.
Zappa, Giuseppe, Len Shaffrey, Kevin I. Hodges, Philip G. Sansom, & David B. Stephenson. (2013). A Multimodel Assessment of Future Projections of North Atlantic and European Extratropical Cyclones in the CMIP5 Climate Models*. Journal of Climate. 26(16). 5846–5862. 290 indexed citations
18.
Clément, Jan, et al.. (2009). Environmental and ecological potential for enzootic cycles of Puumala hantavirus in Great Britain. Epidemiology and Infection. 138(1). 91–98. 17 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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