Saeed Moghimi

1.2k total citations
42 papers, 703 citations indexed

About

Saeed Moghimi is a scholar working on Atmospheric Science, Oceanography and Earth-Surface Processes. According to data from OpenAlex, Saeed Moghimi has authored 42 papers receiving a total of 703 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Atmospheric Science, 26 papers in Oceanography and 15 papers in Earth-Surface Processes. Recurrent topics in Saeed Moghimi's work include Tropical and Extratropical Cyclones Research (26 papers), Ocean Waves and Remote Sensing (19 papers) and Oceanographic and Atmospheric Processes (15 papers). Saeed Moghimi is often cited by papers focused on Tropical and Extratropical Cyclones Research (26 papers), Ocean Waves and Remote Sensing (19 papers) and Oceanographic and Atmospheric Processes (15 papers). Saeed Moghimi collaborates with scholars based in United States, Iran and Germany. Saeed Moghimi's co-authors include Edward Myers, Yinglong Zhang, Fei Ye, Hao‐Cheng Yu, Aron Roland, Jiabi Du, Zhuo Liu, Karinna Nunez, Ali Abdolali and Jim Thomson and has published in prestigious journals such as Journal of Physical Oceanography, Environmental Modelling & Software and Deep Sea Research Part II Topical Studies in Oceanography.

In The Last Decade

Saeed Moghimi

39 papers receiving 689 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saeed Moghimi United States 15 496 422 329 259 64 42 703
Peter Bacopoulos United States 15 405 0.8× 255 0.6× 311 0.9× 186 0.7× 224 3.5× 38 613
Laura Tuomi Finland 16 274 0.6× 578 1.4× 260 0.8× 147 0.6× 55 0.9× 54 719
Jorge Pérez Spain 12 510 1.0× 503 1.2× 291 0.9× 290 1.1× 80 1.3× 17 754
P. R. Shanas India 17 386 0.8× 644 1.5× 245 0.7× 210 0.8× 68 1.1× 32 796
A. T. Cox United States 7 646 1.3× 450 1.1× 435 1.3× 226 0.9× 137 2.1× 8 786
Mercè Casas‐Prat Spain 17 506 1.0× 533 1.3× 358 1.1× 196 0.8× 105 1.6× 24 791
Joseph B. Zambon United States 8 727 1.5× 771 1.8× 347 1.1× 305 1.2× 162 2.5× 15 1.0k
Job Dullaart Netherlands 8 423 0.9× 194 0.5× 158 0.5× 359 1.4× 51 0.8× 12 551
Andrew Saulter United Kingdom 12 313 0.6× 268 0.6× 246 0.7× 189 0.7× 121 1.9× 35 550
Brandy Armstrong United States 5 613 1.2× 672 1.6× 363 1.1× 248 1.0× 188 2.9× 19 929

Countries citing papers authored by Saeed Moghimi

Since Specialization
Citations

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

Fields of papers citing papers by Saeed Moghimi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saeed Moghimi

This figure shows the co-authorship network connecting the top 25 collaborators of Saeed Moghimi. A scholar is included among the top collaborators of Saeed Moghimi 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 Saeed Moghimi. Saeed Moghimi 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.
Zhang, Yinglong, Chin H. Wu, Dmitry Beletsky, et al.. (2025). Cross-scale prediction for the Laurentian Great Lakes. Ocean Modelling. 194. 102512–102512. 1 indexed citations
2.
Zhang, Yinglong, Emanuele Di Lorenzo, Ayumi Fujisaki‐Manome, et al.. (2025). Evaluation of a 3D unstructured grid model for the New York-New Jersey Harbor under different forcing sources. Ocean Modelling. 197. 102598–102598.
3.
Khazaei, Bahram, et al.. (2025). Sensitivity Analysis of a Coastal Ocean Forecast Model to Nearshore Bathymetric Variability. Journal of Hydrologic Engineering. 31(1).
4.
Zhang, Yinglong, Hao‐Cheng Yu, Zhengui Wang, et al.. (2024). Total water level prediction at continental scale: Coastal ocean. Ocean Modelling. 192. 102451–102451. 2 indexed citations
5.
Zhang, Yinglong, Chin H. Wu, Eric J. Anderson, et al.. (2024). Debunking common myths in coastal circulation modeling. Ocean Modelling. 190. 102401–102401. 5 indexed citations
6.
Wirasaet, Damrongsak, William Pringle, Edward D. Zaron, et al.. (2024). Dissipation Scaled Internal Wave Drag in a Global Heterogeneously Coupled Internal/External Mode Total Water Level Model. Journal of Advances in Modeling Earth Systems. 16(12).
7.
Chen, Jing, Yonggang Liu, Robert H. Weisberg, et al.. (2023). Hydrodynamic response to bathymetric changes in Tampa Bay, Florida. Deep Sea Research Part II Topical Studies in Oceanography. 212. 105344–105344. 5 indexed citations
8.
Ye, Fei, Yinglong Zhang, Zhengui Wang, et al.. (2023). A parallel Python-based tool for meshing watershed rivers at continental scale. Environmental Modelling & Software. 166. 105731–105731. 10 indexed citations
9.
Zhang, Yinglong, et al.. (2023). Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0). Geoscientific model development. 16(9). 2565–2581. 12 indexed citations
10.
Dresback, Kendra M., et al.. (2023). Development and Validation of Accumulation Term (Distributed and/or Point Source) in a Finite Element Hydrodynamic Model. Journal of Marine Science and Engineering. 11(2). 248–248. 3 indexed citations
11.
Pringle, William, et al.. (2023). Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation. NOAA Institutional Repository. 2(2). 4 indexed citations
12.
Pringle, William, Damrongsak Wirasaet, Joannes J. Westerink, et al.. (2022). Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model. Journal of Geophysical Research Oceans. 127(5). 15 indexed citations
13.
Ye, Fei, Wei Huang, Yinglong Zhang, et al.. (2021). A cross-scale study for compound flooding processes during Hurricane Florence. Natural hazards and earth system sciences. 21(6). 1703–1719. 40 indexed citations
14.
Abdolali, Ali, Aron Roland, André van der Westhuysen, et al.. (2020). WAVEWATCH III Accuracy and Efficiency within Coupling Framework. 1 indexed citations
15.
Seroka, Greg, Sergey Vinogradov, Edward Myers, et al.. (2020). Extratropical Surge & Tide Operational Forecast System (ESTOFS): Global Upgrade, Future Development, Pacific Enhancement. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
16.
Bakhtyar, R., Kazungu Maitaria, Hassan Mashriqui, et al.. (2020). A New 1D/2D Coupled Modeling Approach for a Riverine‐Estuarine System Under Storm Events: Application to Delaware River Basin. Journal of Geophysical Research Oceans. 125(9). 51 indexed citations
17.
Bakhtyar, R., Kazungu Maitaria, Hassan Mashriqui, et al.. (2019). Regional-Scale Hydrologic and Hydrodynamic Modeling of a Riverine-Estuarine System under Extreme Storms: Application to U.S. East Coast. AGU Fall Meeting Abstracts. 2019. 2 indexed citations
18.
Ye, Fei, Yinglong Zhang, Hao‐Cheng Yu, et al.. (2019). Simulating storm surge and compound flooding events with a creek-to-ocean model: Importance of baroclinic effects. Ocean Modelling. 145. 101526–101526. 81 indexed citations
19.
Farquharson, Gordon, et al.. (2016). An analysis of error in surface current mapping by an along-track interferometric FMCW SAR. 3215–3218. 3 indexed citations
20.
Moghimi, Saeed, et al.. (2014). Estimating effects of terrain attributes on local soil organic carbon content in a semi-arid pastureland. 5(2). 97–106. 2 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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