Conor Murphy

8.2k citations
124 papers · 3.9k · 2 hit papers · h-index 35

Impact in

Papers in

Conor Murphy

119 papers receiving 3.7k citations

Conor Murphy's Hit Papers

Hybrid forecasting: blending climate predictions with AI models 2023 · 93 citations
930+1+3Years since publication50100150

Peers

Conor Murphy
Comparison fields: 5 of 139
  • Global and Planetary Change 2.7k
  • Water Science and Technology 1.5k
  • Atmospheric Science 959
  • Environmental Engineering 454
  • Health, Toxicology and Mutagenesis 275
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Conor Murphy relative to Justin Mankin United States Justin Mankin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Conor Murphy

Since Specialization
Citations

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

Fields of papers citing papers by Conor Murphy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Conor Murphy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Conor Murphy Line = papers co-authored together Conor Murphy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 124 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017235
2 2011204
3 2012180
4
Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management
Hit paper breakdown →
2021170
5 2017140
6 2017107
7 2019104
8 2014100
9 201499
10 202096
11
Hybrid forecasting: blending climate predictions with AI models
Hit paper breakdown →
202393
12 201985
13 201682
14 202079
15 200672
16 201470
17 201861
18 202057
19 201756
20 201354

About Conor Murphy

Conor Murphy is a scholar working on Global and Planetary Change, Water Science and Technology, Atmospheric Science, Sociology and Political Science and Environmental Engineering, having authored 124 papers that have together received 3.9k indexed citations. Recurring topics across this work include Hydrology and Drought Analysis (58 papers), Hydrology and Watershed Management Studies (54 papers), Climate variability and models (51 papers), Flood Risk Assessment and Management (35 papers), Meteorological Phenomena and Simulations (19 papers), Tree-ring climate responses (10 papers), Climate Change, Adaptation, Migration (10 papers) and Plant Water Relations and Carbon Dynamics (8 papers). The work is most often cited by research in Global and Planetary Change (2.7k citations), Water Science and Technology (1.5k citations), Atmospheric Science (959 citations), Environmental Engineering (454 citations) and Health, Toxicology and Mutagenesis (275 citations). Conor Murphy has collaborated with scholars based in Ireland, United Kingdom and Spain. Frequent co-authors include Robert L. Wilby, Tom Matthews, John Sweeney, Shaun Harrigan, Satish Bastola, Irene Lorenzoni, Saeed Golian, Julia Hall, Darren Clarke and Tara Quinn. Their work appears in journals such as International Journal of Climatology, Hydrology and earth system sciences, Environmental Research Letters, Water Resources Research and Nature Climate Change.

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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