Matjaž Ličer

903 total citations
29 papers, 481 citations indexed

About

Matjaž Ličer is a scholar working on Oceanography, Atmospheric Science and Global and Planetary Change. According to data from OpenAlex, Matjaž Ličer has authored 29 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Oceanography, 9 papers in Atmospheric Science and 8 papers in Global and Planetary Change. Recurrent topics in Matjaž Ličer's work include Oceanographic and Atmospheric Processes (12 papers), Ocean Waves and Remote Sensing (6 papers) and Meteorological Phenomena and Simulations (5 papers). Matjaž Ličer is often cited by papers focused on Oceanographic and Atmospheric Processes (12 papers), Ocean Waves and Remote Sensing (6 papers) and Meteorological Phenomena and Simulations (5 papers). Matjaž Ličer collaborates with scholars based in Slovenia, Italy and Belgium. Matjaž Ličer's co-authors include Rudolf Podgornik, Alexander Barth, Jean-Marie Beckers, Aïda Alvera Azcarate, Vlado Malačič, Martin Vodopıvec, Simone Cosoli, Matej Kristan, P. Smerkol and Baptiste Mourre and has published in prestigious journals such as Physical Review Letters, Frontiers in Microbiology and Marine Pollution Bulletin.

In The Last Decade

Matjaž Ličer

26 papers receiving 466 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matjaž Ličer Slovenia 13 252 167 106 55 54 29 481
Holly S. Morris United States 11 58 0.2× 554 3.3× 385 3.6× 7 0.1× 12 0.2× 14 717
Manoj K. Mishra India 13 56 0.2× 110 0.7× 137 1.3× 4 0.1× 43 0.8× 49 448
John Bognar United States 14 50 0.2× 193 1.2× 259 2.4× 14 0.3× 127 2.4× 29 538
Johannes Becherer Germany 14 310 1.2× 222 1.3× 57 0.5× 6 0.1× 117 2.2× 21 446
Jing Tao China 8 35 0.1× 134 0.8× 65 0.6× 20 0.4× 101 1.9× 23 384
Gerben Boer Netherlands 14 295 1.2× 194 1.2× 70 0.7× 6 0.1× 215 4.0× 29 663
Melanie Summit United States 8 78 0.3× 103 0.6× 25 0.2× 8 0.1× 235 4.4× 8 531
Haiyan Li China 9 188 0.7× 128 0.8× 29 0.3× 2 0.0× 14 0.3× 28 407
Rūta Barisevičiūtė Lithuania 11 63 0.3× 48 0.3× 81 0.8× 25 0.5× 120 2.2× 37 341
Hansol D. Lee United States 12 44 0.2× 297 1.8× 206 1.9× 2 0.0× 7 0.1× 20 397

Countries citing papers authored by Matjaž Ličer

Since Specialization
Citations

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

Fields of papers citing papers by Matjaž Ličer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matjaž Ličer

This figure shows the co-authorship network connecting the top 25 collaborators of Matjaž Ličer. A scholar is included among the top collaborators of Matjaž Ličer 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 Matjaž Ličer. Matjaž Ličer 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.
Zavrtanik, Vitjan, et al.. (2025). CRITER 1.0: a coarse reconstruction with iterative refinement network for sparse spatio-temporal satellite data. Geoscientific model development. 18(17). 5549–5573.
2.
Ličer, Matjaž, Matej Kristan, Ilja Maljutenko, et al.. (2025). Application of the HIDRA2 deep-learning model for sea level forecasting along the Estonian coast of the Baltic Sea. Ocean science. 21(4). 1315–1327.
3.
Mihanović, Hrvoje, et al.. (2025). HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures. Geoscientific model development. 18(3). 605–620. 3 indexed citations
4.
Ricchi, Antonio, et al.. (2024). DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin. Geoscientific model development. 17(12). 4705–4725. 3 indexed citations
5.
Kristan, Matej, et al.. (2023). HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic. Geoscientific model development. 16(1). 271–288. 9 indexed citations
6.
7.
Fadeev, Eduard, et al.. (2022). Bacterial Indicators Are Ubiquitous Members of Pelagic Microbiome in Anthropogenically Impacted Coastal Ecosystem. Frontiers in Microbiology. 12. 765091–765091. 19 indexed citations
8.
Žust, Lojze, et al.. (2021). HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic. Geoscientific model development. 14(4). 2057–2074. 17 indexed citations
9.
Ferrarin, Christian, Andrea Valentini, Martin Vodopıvec, et al.. (2020). Integrated sea storm management strategy: the 29 October 2018 event in the Adriatic Sea. Natural hazards and earth system sciences. 20(1). 73–93. 33 indexed citations
10.
11.
Ličer, Matjaž, et al.. (2020). Lagrangian modelling of a person lost at sea during the Adriatic scirocco storm of 29 October 2018. Natural hazards and earth system sciences. 20(8). 2335–2349. 15 indexed citations
12.
Barth, Alexander, Aïda Alvera Azcarate, Matjaž Ličer, & Jean-Marie Beckers. (2020). DINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations. Geoscientific model development. 13(3). 1609–1622. 87 indexed citations
13.
Barth, Alexander, Aïda Alvera Azcarate, Matjaž Ličer, & Jean-Marie Beckers. (2020). A convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations (DINCAE). Open Repository and Bibliography (University of Liège). 4 indexed citations
14.
Ličer, Matjaž, et al.. (2018). Numerical modelling of mercury evasion in a two-layered Adriatic Sea using a coupled atmosphere-ocean model. Marine Pollution Bulletin. 135. 1164–1173. 6 indexed citations
15.
Ličer, Matjaž, et al.. (2018). Impact of two‐way coupling and sea‐surface temperature on precipitation forecasts in regional atmosphere and ocean models. Quarterly Journal of the Royal Meteorological Society. 145(718). 228–242. 21 indexed citations
16.
Ličer, Matjaž, P. Smerkol, Anneta Mantziafou, et al.. (2016). Modeling the ocean and atmosphere during an extreme bora event in northern Adriatic using one-way and two-way atmosphere–ocean coupling. Ocean science. 12(1). 71–86. 48 indexed citations
17.
Malačič, Vlado, et al.. (2013). High-resolution pollutant dispersion modelling in contaminated coastal sites. Environmental Research. 125. 103–112. 16 indexed citations
18.
Ličer, Matjaž & Rudolf Podgornik. (2010). Polyelectrolyte-mediated bridging interactions: columnar macromolecular phases. Journal of Physics Condensed Matter. 22(41). 414102–414102. 11 indexed citations
19.
Podgornik, Rudolf & Matjaž Ličer. (2006). Polyelectrolyte bridging interactions between charged macromolecules. Current Opinion in Colloid & Interface Science. 11(5). 273–279. 74 indexed citations
20.
Omerzu, A., Matjaž Ličer, T. Mertelj, V. V. Kabanov, & D. Mihailović. (2004). Hole Interactions with Molecular Vibrations on DNA. Physical Review Letters. 93(21). 218101–218101. 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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