Subimal Ghosh

9.1k total citations · 1 hit paper
168 papers, 6.6k citations indexed

About

Subimal Ghosh is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Subimal Ghosh has authored 168 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 135 papers in Global and Planetary Change, 70 papers in Atmospheric Science and 40 papers in Water Science and Technology. Recurrent topics in Subimal Ghosh's work include Climate variability and models (101 papers), Meteorological Phenomena and Simulations (45 papers) and Hydrology and Watershed Management Studies (38 papers). Subimal Ghosh is often cited by papers focused on Climate variability and models (101 papers), Meteorological Phenomena and Simulations (45 papers) and Hydrology and Watershed Management Studies (38 papers). Subimal Ghosh collaborates with scholars based in India, United States and Germany. Subimal Ghosh's co-authors include Subhankar Karmakar, P. P. Mujumdar, Amey Pathak, Vittal Hari, Raghu Murtugudde, Mathew Koll Roxy, S. Kannan, P. P. Mujumdar, Auroop R. Ganguly and A. S. Sahana and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Geophysical Research Atmospheres.

In The Last Decade

Subimal Ghosh

157 papers receiving 6.4k citations

Hit Papers

A threefold rise in widespread extreme rain events over c... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subimal Ghosh India 46 5.2k 3.0k 1.7k 1.4k 638 168 6.6k
Alex J. Cannon Canada 42 5.0k 1.0× 3.2k 1.1× 2.4k 1.4× 1.4k 1.0× 556 0.9× 152 7.5k
Jianfeng Li China 41 3.6k 0.7× 1.8k 0.6× 1.3k 0.7× 831 0.6× 424 0.7× 157 4.9k
Chris Kilsby United Kingdom 47 5.3k 1.0× 2.3k 0.8× 2.8k 1.6× 1.1k 0.8× 282 0.4× 151 6.9k
Vimal Mishra India 61 8.2k 1.6× 3.2k 1.1× 3.4k 2.0× 1.7k 1.2× 1.2k 1.9× 189 10.6k
Harald Kunstmann Germany 49 4.8k 0.9× 3.5k 1.2× 2.4k 1.4× 1.4k 1.0× 674 1.1× 296 7.2k
Hannah Cloke United Kingdom 47 5.4k 1.1× 2.8k 0.9× 3.6k 2.1× 1.9k 1.4× 181 0.3× 167 7.3k
Thian Yew Gan Canada 48 5.1k 1.0× 2.4k 0.8× 3.1k 1.8× 1.4k 1.1× 462 0.7× 173 7.3k
Rohini Kumar Germany 51 5.3k 1.0× 1.6k 0.5× 4.6k 2.7× 2.0k 1.5× 484 0.8× 194 8.4k
Seth Westra Australia 47 9.8k 1.9× 5.2k 1.7× 3.5k 2.1× 1.1k 0.8× 874 1.4× 128 11.9k
Hossein Tabari Belgium 51 6.7k 1.3× 2.0k 0.7× 2.9k 1.7× 2.0k 1.4× 873 1.4× 117 8.6k

Countries citing papers authored by Subimal Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by Subimal Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subimal Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Subimal Ghosh. A scholar is included among the top collaborators of Subimal Ghosh 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 Subimal Ghosh. Subimal Ghosh 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.
Ghosh, Subimal, et al.. (2025). Role of Micrometeorological Memory in Modulating Sub‐Daily Scale Variability of Net Ecosystem Exchange. Journal of Geophysical Research Biogeosciences. 130(1). 1 indexed citations
2.
Mandal, Mamun, Anamika Roy, Subimal Ghosh, et al.. (2025). Assessing the Influences of Leaf Functional Traits on Plant Performances Under Dust Deposition and Microplastic Retention. Atmosphere. 16(7). 861–861.
3.
Ghosh, Subimal, et al.. (2025). Possible influences of Prosopis juliflora on groundwater resources in Gujarat. Journal of Hydrology. 662. 133993–133993.
4.
5.
Siems, Steven T., et al.. (2023). Aerosol-heavy precipitation relationship within monsoonal regimes in the Western Himalayas. Atmospheric Research. 288. 106728–106728. 2 indexed citations
6.
Ghosh, Subimal, et al.. (2023). The relative role of soil moisture and vapor pressure deficit in affecting the Indian vegetation productivity. Environmental Research Letters. 18(6). 64012–64012. 32 indexed citations
7.
Shastri, Hiteshri, et al.. (2023). A Novel Response Priority Framework for an Urban Coastal Catchment Using Global Weather Forecasts‐Based Improved Flood Risk Estimates. Journal of Geophysical Research Atmospheres. 128(17). 5 indexed citations
8.
Patel, Pratiman, Sajad Jamshidi, Raghu Nadimpalli, et al.. (2023). Impact of Urban Representation on Simulation of Hurricane Rainfall. Geophysical Research Letters. 50(21). 2 indexed citations
9.
Ghosh, Subimal, et al.. (2023). Indian Summer Monsoon Rainfall in a changing climate: a review. Journal of Water and Climate Change. 14(4). 1061–1088. 21 indexed citations
10.
Ashfaq, Moetasim, Nathaniel C. Johnson, Fred Kucharski, et al.. (2023). The influence of natural variability on extreme monsoons in Pakistan. npj Climate and Atmospheric Science. 6(1). 8 indexed citations
11.
Jackson, Christopher, et al.. (2022). Is flood to drip irrigation a solution to groundwater depletion in the Indo-Gangetic plain?. Environmental Research Letters. 17(10). 104002–104002. 10 indexed citations
12.
Rehana, S., Chandra Rupa Rajulapati, Subimal Ghosh, Subhankar Karmakar, & P. P. Mujumdar. (2020). Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India. Water. 12(6). 1793–1793. 18 indexed citations
13.
Pathak, Amey, J. Indu, Sharad K. Jain, et al.. (2020). Observed Evidence for Steep Rise in the Extreme Flow of Western Himalayan Rivers. Geophysical Research Letters. 47(15). 27 indexed citations
14.
Salvi, Kaustubh & Subimal Ghosh. (2019). A kaleidoscopic research memoir on Indian summer monsoon rainfall. MAUSAM. 70(2). 293–298. 2 indexed citations
15.
Mohanty, Mohit Prakash, Vittal Hari, Vinay Yadav, et al.. (2019). A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions. Journal of Environmental Management. 255. 109733–109733. 74 indexed citations
16.
Sahana, A. S. & Subimal Ghosh. (2018). An Improved Prediction of Indian Summer Monsoon Onset From State‐of‐the‐Art Dynamic Model Using Physics‐Guided Data‐Driven Approach. Geophysical Research Letters. 45(16). 8510–8518. 8 indexed citations
17.
Mazdiyasni, Omid, Amir AghaKouchak, Steven J. Davis, et al.. (2017). Increasing probability of mortality during Indian heat waves. Science Advances. 3(6). e1700066–e1700066. 296 indexed citations
18.
Ghosh, Subimal, Hiteshri Shastri, Amey Pathak, & Supantha Paul. (2017). Changing Pattern of Indian Monsoon Extremes: Global and Local Factors. EGUGA. 2392. 1 indexed citations
19.
Mujumdar, P. P., Subimal Ghosh, & Deepashree Raje. (2009). Hydro-meteorological predictions from GCM simulations: downscaling techniques and uncertainty modelling. IAHS-AISH publication. 333. 165–175. 2 indexed citations
20.
Ghosh, Subimal & P. P. Mujumdar. (2007). Modeling GCM and Scenario Uncertainty: An Imprecise Probability Approach.. Indian International Conference on Artificial Intelligence. 836–846. 1 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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