Rosa Barciela

2.1k total citations
29 papers, 1.2k citations indexed

About

Rosa Barciela is a scholar working on Oceanography, Global and Planetary Change and Sociology and Political Science. According to data from OpenAlex, Rosa Barciela has authored 29 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Oceanography, 18 papers in Global and Planetary Change and 2 papers in Sociology and Political Science. Recurrent topics in Rosa Barciela's work include Marine and coastal ecosystems (19 papers), Oceanographic and Atmospheric Processes (15 papers) and Marine Biology and Ecology Research (7 papers). Rosa Barciela is often cited by papers focused on Marine and coastal ecosystems (19 papers), Oceanographic and Atmospheric Processes (15 papers) and Marine Biology and Ecology Research (7 papers). Rosa Barciela collaborates with scholars based in United Kingdom, United States and Spain. Rosa Barciela's co-authors include Shubha Sathyendranath, Samantha Lavender, Robert J. W. Brewin, Takafumi Hirata, Nick J. Hardman-Mountford, Beatriz Mouriño, Natalia González, Emilio Marañón, M. Varela and P. M. Holligan and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and Scientific Reports.

In The Last Decade

Rosa Barciela

29 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rosa Barciela United Kingdom 17 1.0k 489 335 125 109 29 1.2k
Marlenne Manzano‐Sarabia Mexico 14 706 0.7× 442 0.9× 301 0.9× 193 1.5× 92 0.8× 26 992
Mini Raman India 16 453 0.4× 282 0.6× 235 0.7× 82 0.7× 56 0.5× 63 657
Wen Long United States 15 425 0.4× 190 0.4× 209 0.6× 92 0.7× 108 1.0× 31 712
Emma L. Cavan United Kingdom 18 880 0.9× 389 0.8× 523 1.6× 158 1.3× 124 1.1× 29 1.3k
Johannes Rick Germany 14 365 0.4× 211 0.4× 274 0.8× 53 0.4× 113 1.0× 54 710
Annie Fiandrino France 17 348 0.3× 280 0.6× 210 0.6× 43 0.3× 147 1.3× 49 753
Yoav Lehahn Israel 21 676 0.7× 381 0.8× 362 1.1× 383 3.1× 102 0.9× 40 1.2k
Kostas Tsiaras Greece 20 427 0.4× 487 1.0× 263 0.8× 82 0.7× 34 0.3× 58 1.0k
Fabrizio Bernardi Aubry Italy 21 941 0.9× 373 0.8× 604 1.8× 59 0.5× 251 2.3× 48 1.3k
Mingzhu Fu China 19 853 0.8× 205 0.4× 322 1.0× 107 0.9× 63 0.6× 40 995

Countries citing papers authored by Rosa Barciela

Since Specialization
Citations

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

Fields of papers citing papers by Rosa Barciela

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rosa Barciela

This figure shows the co-authorship network connecting the top 25 collaborators of Rosa Barciela. A scholar is included among the top collaborators of Rosa Barciela 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 Rosa Barciela. Rosa Barciela 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.
Mitchell, Dann, Y. T. Eunice Lo, Oliver Andrews, et al.. (2024). Expert judgement reveals current and emerging UK climate-mortality burden. The Lancet Planetary Health. 8(9). e684–e694. 5 indexed citations
2.
Catto, Jennifer L., et al.. (2024). Quantifying causal teleconnections to drought and fire risks in Indonesian Borneo. International Journal of Climatology. 44(6). 2087–2105. 1 indexed citations
3.
Robbins, Joanne, et al.. (2024). Generating weather pattern definitions over South Africa suitable for future use in impact‐orientated medium‐range forecasting. International Journal of Climatology. 44(5). 1513–1529. 4 indexed citations
4.
Usmani, Moiz, et al.. (2023). Combating cholera by building predictive capabilities for pathogenic Vibrio cholerae in Yemen. Scientific Reports. 13(1). 2255–2255. 23 indexed citations
5.
Roberts, Hugh, et al.. (2023). New narratives for a healthy planet: creative writing and art projects reveal We Still Have a Chance. The Lancet Planetary Health. 7(8). e646–e647. 1 indexed citations
6.
Sharpe, Richard A., Rosa Barciela, Gordon Nichols, et al.. (2020). Marine harmful algal blooms and human health: A systematic scoping review. Harmful Algae. 98. 101901–101901. 82 indexed citations
7.
Tinker, Jonathan, et al.. (2018). What are the prospects for seasonal prediction of the marine environment of the North-west European Shelf?. Ocean science. 14(4). 887–909. 8 indexed citations
8.
Ford, David, Johan van der Molen, Kieran Hyder, et al.. (2017). Observing and modelling phytoplankton community structure in the North Sea. Biogeosciences. 14(6). 1419–1444. 27 indexed citations
9.
Ford, David & Rosa Barciela. (2017). Global marine biogeochemical reanalyses assimilating two different sets of merged ocean colour products. Remote Sensing of Environment. 203. 40–54. 35 indexed citations
10.
Ford, David, Johan van der Molen, Kieran Hyder, et al.. (2016). Observing and modelling phytoplankton community structure in theNorth Sea: can ERSEM-type models simulate biodiversity?. 2 indexed citations
11.
Gehlen, Marion, Rosa Barciela, Laurent Bertino, et al.. (2015). Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments. Journal of Operational Oceanography. 8(sup1). s168–s187. 54 indexed citations
12.
Kwiatkowski, Lester, Andrew Yool, J. Icarus Allen, et al.. (2014). iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework. Biogeosciences. 11(24). 7291–7304. 63 indexed citations
13.
Edwards, K. P., Rosa Barciela, & Momme Butenschön. (2012). Validation of the NEMO-ERSEM operational ecosystem model for the North West European Continental Shelf. Ocean science. 8(6). 983–1000. 65 indexed citations
14.
Ford, David, K. P. Edwards, Daniel J. Lea, et al.. (2012). Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model. Ocean science. 8(5). 751–771. 44 indexed citations
15.
Sykes, Peter & Rosa Barciela. (2012). Assessment and development of a sediment model within an operational system. Journal of Geophysical Research Atmospheres. 117(C4). 17 indexed citations
16.
Barciela, Rosa, et al.. (2011). An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data. Ocean science. 7(4). 445–454. 6 indexed citations
17.
Brewin, Robert J. W., Shubha Sathyendranath, Takafumi Hirata, et al.. (2010). A three-component model of phytoplankton size class for the Atlantic Ocean. Ecological Modelling. 221(11). 1472–1483. 240 indexed citations
18.
Hardman-Mountford, Nicholas J., Gerald Moore, Dorothée C. E. Bakker, et al.. (2008). An operational monitoring system to provide indicators of CO2-related variables in the ocean. ICES Journal of Marine Science. 65(8). 1498–1503. 22 indexed citations
19.
Hemmings, John, Rosa Barciela, & Michael J. Bell. (2007). A material balancing scheme for ocean colour data assimilation. ePrints Soton (University of Southampton). 1 indexed citations
20.
Barciela, Rosa, Emilio García‐Roselló, & Emilio Fernández. (1999). Modelling primary production in a coastal embayment affected by upwelling using dynamic ecosystem models and artificial neural networks. Ecological Modelling. 120(2-3). 199–211. 39 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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