Jonathan J. Day

3.3k total citations
41 papers, 1.5k citations indexed

About

Jonathan J. Day is a scholar working on Atmospheric Science, Global and Planetary Change and Sociology and Political Science. According to data from OpenAlex, Jonathan J. Day has authored 41 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Atmospheric Science, 28 papers in Global and Planetary Change and 6 papers in Sociology and Political Science. Recurrent topics in Jonathan J. Day's work include Arctic and Antarctic ice dynamics (31 papers), Climate variability and models (24 papers) and Climate change and permafrost (21 papers). Jonathan J. Day is often cited by papers focused on Arctic and Antarctic ice dynamics (31 papers), Climate variability and models (24 papers) and Climate change and permafrost (21 papers). Jonathan J. Day collaborates with scholars based in United Kingdom, United States and Germany. Jonathan J. Day's co-authors include Ed Hawkins, Steffen Tietsche, Kevin I. Hodges, Sarah Keeley, J. D. Annan, Ayako Abe‐Ouchi, J. C. Hargreaves, Virginie Guémas, Irina Sandu and Helge Goessling and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Jonathan J. Day

40 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan J. Day United Kingdom 20 1.4k 925 192 103 85 41 1.5k
R. Cullen Netherlands 12 1.3k 0.9× 194 0.2× 320 1.7× 82 0.8× 27 0.3× 30 1.5k
M. A. Tschudi United States 12 956 0.7× 349 0.4× 54 0.3× 58 0.6× 34 0.4× 15 995
Katharine Giles United Kingdom 10 1.5k 1.1× 244 0.3× 264 1.4× 204 2.0× 42 0.5× 15 1.6k
Wolfgang Dorn Germany 18 820 0.6× 528 0.6× 112 0.6× 50 0.5× 9 0.1× 41 869
Thomas Armitage United States 18 1.1k 0.8× 281 0.3× 409 2.1× 297 2.9× 18 0.2× 29 1.2k
Yoshikazu Fukuda Japan 7 716 0.5× 883 1.0× 417 2.2× 13 0.1× 4 0.0× 17 1.0k
Dewi Le Bars Netherlands 15 371 0.3× 398 0.4× 330 1.7× 19 0.2× 39 0.5× 32 678
W. B. Tucker United States 24 1.7k 1.2× 217 0.2× 168 0.9× 172 1.7× 32 0.4× 49 1.7k
Paul A. Dodd Norway 13 567 0.4× 140 0.2× 325 1.7× 244 2.4× 19 0.2× 30 760
Jeremy Fyke United States 16 708 0.5× 292 0.3× 58 0.3× 31 0.3× 8 0.1× 32 774

Countries citing papers authored by Jonathan J. Day

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan J. Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan J. Day. 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 Jonathan J. Day. The network helps show where Jonathan J. Day may publish in the future.

Co-authorship network of co-authors of Jonathan J. Day

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan J. Day. A scholar is included among the top collaborators of Jonathan J. Day 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 Jonathan J. Day. Jonathan J. Day 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.
Hodges, Kevin I., et al.. (2024). The risk of synoptic-scale Arctic cyclones to shipping. Natural hazards and earth system sciences. 24(6). 2115–2132. 2 indexed citations
2.
Uttal, Taneil, Leslie M. Hartten, S. S. Khalsa, et al.. (2024). Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics. Geoscientific model development. 17(13). 5225–5247.
3.
Solomon, Amy, Matthew D. Shupe, Gunilla Svensson, et al.. (2023). The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign. Elementa Science of the Anthropocene. 11(1). 21 indexed citations
4.
Vüllers, Jutta, Peggy Achtert, Jonathan J. Day, et al.. (2023). Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System. Atmospheric chemistry and physics. 23(8). 4819–4847. 9 indexed citations
5.
Svensson, Gunilla, Matthew D. Shupe, Felix Pithan, et al.. (2023). Warm air intrusions reaching the MOSAiC expedition in April 2020—The YOPP targeted observing period (TOP). Elementa Science of the Anthropocene. 11(1). 12 indexed citations
6.
Arduini, Gabriele, Sarah Keeley, Jonathan J. Day, et al.. (2022). On the Importance of Representing Snow Over Sea‐Ice for Simulating the Arctic Boundary Layer. Journal of Advances in Modeling Earth Systems. 14(7). 17 indexed citations
7.
Luo, Hao, et al.. (2022). The Challenge of Arctic Sea Ice Thickness Prediction by ECMWF on Subseasonal Time Scales. Geophysical Research Letters. 49(8). 11 indexed citations
8.
Hodges, Kevin I., et al.. (2022). The composite development and structure of intense synoptic-scale Arctic cyclones. Weather and Climate Dynamics. 3(3). 1097–1112. 15 indexed citations
9.
Day, Jonathan J., Sarah Keeley, Gabriele Arduini, et al.. (2022). Benefits and challenges of dynamic sea ice for weather forecasts. Weather and Climate Dynamics. 3(3). 713–731. 8 indexed citations
10.
Young, Gillian, Jutta Vüllers, Peggy Achtert, et al.. (2021). Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System. 1 indexed citations
11.
Day, Jonathan J., Gabriele Arduini, Irina Sandu, et al.. (2020). Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships. Journal of Advances in Modeling Earth Systems. 12(12). 12 indexed citations
12.
Arduini, Gabriele, Gianpaolo Balsamo, Emanuel Dutra, et al.. (2019). Impact of a Multi‐Layer Snow Scheme on Near‐Surface Weather Forecasts. Journal of Advances in Modeling Earth Systems. 11(12). 4687–4710. 43 indexed citations
13.
Day, Jonathan J., Irina Sandu, Linus Magnusson, et al.. (2019). Increased Arctic influence on the midlatitude flow during Scandinavian Blocking episodes. Quarterly Journal of the Royal Meteorological Society. 145(725). 3846–3862. 15 indexed citations
14.
Day, Jonathan J. & Kevin I. Hodges. (2018). Growing Land‐Sea Temperature Contrast and the Intensification of Arctic Cyclones. Geophysical Research Letters. 45(8). 3673–3681. 51 indexed citations
15.
Day, Jonathan J., Marika M. Holland, & Kevin I. Hodges. (2018). Correction to: Seasonal differences in the response of Arctic cyclones to climate change in CESM1. Climate Dynamics. 50(9-10). 3905–3907. 2 indexed citations
16.
Day, Jonathan J., Marika M. Holland, & Kevin I. Hodges. (2017). Seasonal differences in the response of Arctic cyclones to climate change in CESM1. Climate Dynamics. 50(9-10). 3885–3903. 38 indexed citations
17.
Day, Jonathan J., et al.. (2016). Estimating the extent of Antarctic summer sea ice during the Heroic Age of Antarctic Exploration. ˜The œcryosphere. 10(6). 2721–2730. 13 indexed citations
18.
Day, Jonathan J., Steffen Tietsche, Matthew Collins, et al.. (2016). The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1. Geoscientific model development. 9(6). 2255–2270. 25 indexed citations
19.
Day, Jonathan J., et al.. (2016). Estimating the extent of Antarctic summer sea ice during the Heroic Age of Exploration. CentAUR (University of Reading). 2 indexed citations
20.
Day, Jonathan J., Steffen Tietsche, Matthew Collins, et al.. (2015). The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set. Open Research Exeter (University of Exeter). 3 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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