Mojtaba Sadeghi

829 total citations
14 papers, 539 citations indexed

About

Mojtaba Sadeghi is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Mojtaba Sadeghi has authored 14 papers receiving a total of 539 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Atmospheric Science, 9 papers in Global and Planetary Change and 1 paper in Oceanography. Recurrent topics in Mojtaba Sadeghi's work include Precipitation Measurement and Analysis (13 papers), Meteorological Phenomena and Simulations (11 papers) and Climate variability and models (7 papers). Mojtaba Sadeghi is often cited by papers focused on Precipitation Measurement and Analysis (13 papers), Meteorological Phenomena and Simulations (11 papers) and Climate variability and models (7 papers). Mojtaba Sadeghi collaborates with scholars based in United States, Iran and Italy. Mojtaba Sadeghi's co-authors include Soroosh Sorooshian, Phu Nguyen, Kuolin Hsu, Dan Braithwaite, Ata Akbari Asanjan, Matin Rahnamay Naeini, Vesta Afzali Gorooh, E. J. Shearer, Feng Liu and David T. Bolvin and has published in prestigious journals such as Journal of Hydrology, Remote Sensing and Environmental Modelling & Software.

In The Last Decade

Mojtaba Sadeghi

13 papers receiving 531 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mojtaba Sadeghi United States	10	409	339	125	81	27	14	539
Tim Raupach Switzerland	14	454 1.1×	300 0.9×	160 1.3×	83 1.0×	70 2.6×	28	624
David Fairbairn United Kingdom	11	384 0.9×	375 1.1×	252 2.0×	88 1.1×	8 0.3×	18	534
Brian C. Ancell United States	15	551 1.3×	684 2.0×	176 1.4×	101 1.2×	27 1.0×	32	807
Sergio Fernández‐González Spain	19	679 1.7×	659 1.9×	145 1.2×	36 0.4×	92 3.4×	41	837
Feimin Zhang China	12	300 0.7×	204 0.6×	79 0.6×	28 0.3×	25 0.9×	35	368
José C. Fernández‐Alvarez Spain	13	285 0.7×	327 1.0×	67 0.5×	35 0.4×	15 0.6×	52	422
Trevor I. Alcott United States	11	432 1.1×	396 1.2×	68 0.5×	28 0.3×	15 0.6×	20	513
Robert M. Rabin United States	13	534 1.3×	489 1.4×	114 0.9×	18 0.2×	14 0.5×	24	636
Vagner Anabor Brazil	11	251 0.6×	234 0.7×	98 0.8×	15 0.2×	13 0.5×	43	328
M. Kerschgens Germany	12	242 0.6×	263 0.8×	102 0.8×	21 0.3×	14 0.5×	28	376

Countries citing papers authored by Mojtaba Sadeghi

Since Specialization

Citations

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

Fields of papers citing papers by Mojtaba Sadeghi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mojtaba Sadeghi

This figure shows the co-authorship network connecting the top 25 collaborators of Mojtaba Sadeghi. A scholar is included among the top collaborators of Mojtaba Sadeghi 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 Mojtaba Sadeghi. Mojtaba Sadeghi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Ciabatta, Luca, et al.. (2025). HR-PrecipNet: A machine learning framework for 1-km high-resolution satellite precipitation estimation. Journal of Hydrology. 658. 133217–133217.

Sadeghi, Mojtaba, et al.. (2022). The Application of PERSIANN Family Datasets for Hydrological Modeling. Remote Sensing. 14(15). 3675–3675. 14 indexed citations

Mallakpour, Iman, Mojtaba Sadeghi, Ata Akbari Asanjan, et al.. (2022). Discrepancies in changes in precipitation characteristics over the contiguous United States based on six daily gridded precipitation datasets. Weather and Climate Extremes. 36. 100433–100433. 19 indexed citations

Sadeghi, Mojtaba, Phu Nguyen, Matin Rahnamay Naeini, et al.. (2021). PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies. Scientific Data. 8(1). 157–157. 112 indexed citations

Sadeghi, Mojtaba, E. J. Shearer, Vesta Afzali Gorooh, et al.. (2021). Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019). Journal of Hydrology. 600. 126569–126569. 20 indexed citations

Sadeghi, Mojtaba, Phung‐Anh Nguyen, Kuolin Hsu, & Soroosh Sorooshian. (2020). Application of Deep Neural Networks and Geographical Information for Improving the Near Real-time Precipitation Estimation Products. AGU Fall Meeting Abstracts. 2020. 1 indexed citations

Nguyen, Phu, Mohammed Ombadi, Vesta Afzali Gorooh, et al.. (2020). PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset. Journal of Hydrometeorology. 21(12). 2893–2906. 92 indexed citations

Sadeghi, Mojtaba, Phu Nguyen, Kuolin Hsu, & Soroosh Sorooshian. (2020). Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information. Environmental Modelling & Software. 134. 104856–104856. 69 indexed citations

Sadeghi, Mojtaba, Negin Hayatbini, Vesta Afzali Gorooh, et al.. (2020). Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset. Remote Sensing. 12(10). 1584–1584. 28 indexed citations

10.

Sadeghi, Mojtaba, et al.. (2019). Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR). AGUFM. 2019. 6 indexed citations

11.

Sadeghi, Mojtaba, Ata Akbari Asanjan, Phu Nguyen, et al.. (2019). PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks. Journal of Hydrometeorology. 20(12). 2273–2289. 130 indexed citations

12.

Sadeghi, Mojtaba, Ata Akbari Asanjan, Vesta Afzali Gorooh, et al.. (2019). Evaluation of PERSIANN-CDR Constructed Using GPCP V2.2 and V2.3 and A Comparison with TRMM 3B42 V7 and CPC Unified Gauge-Based Analysis in Global Scale. Remote Sensing. 11(23). 2755–2755. 22 indexed citations

13.

Sadeghi, Mojtaba. (2018). Assessment of the PERSIANN-CDR Products Bias-corrected with the GPCP Datasets Versions 2.2 & 2.3. 4 indexed citations

14.

Sadeghi, Mojtaba & Feng Liu. (2005). Coupled Fluid-Structure Simulation for Turbomachinery Blade Rows. 43rd AIAA Aerospace Sciences Meeting and Exhibit. 22 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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