Agniv Sengupta

432 total citations
17 papers, 212 citations indexed

About

Agniv Sengupta is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Agniv Sengupta has authored 17 papers receiving a total of 212 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Atmospheric Science, 15 papers in Global and Planetary Change and 5 papers in Environmental Engineering. Recurrent topics in Agniv Sengupta's work include Meteorological Phenomena and Simulations (14 papers), Climate variability and models (13 papers) and Hydrological Forecasting Using AI (5 papers). Agniv Sengupta is often cited by papers focused on Meteorological Phenomena and Simulations (14 papers), Climate variability and models (13 papers) and Hydrological Forecasting Using AI (5 papers). Agniv Sengupta collaborates with scholars based in United States, India and Lebanon. Agniv Sengupta's co-authors include Sumant Nigam, Alfredo Ruiz‐Barradas, Duane E. Waliser, Elias Massoud, Colin Raymond, Bin Guan, Huikyo Lee, Vicky Espinoza, Adrienne Wootten and Luca Delle Monache and has published in prestigious journals such as Journal of Climate, Water Resources Research and Geophysical Research Letters.

In The Last Decade

Agniv Sengupta

15 papers receiving 205 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Agniv Sengupta United States 8 170 139 41 27 24 17 212
Rita Nogherotto Italy 9 257 1.5× 190 1.4× 27 0.7× 25 0.9× 36 1.5× 15 297
Tim Kruschke Germany 11 261 1.5× 227 1.6× 44 1.1× 28 1.0× 44 1.8× 29 314
Chibuike Chiedozie Ibebuchi United States 10 204 1.2× 170 1.2× 47 1.1× 28 1.0× 22 0.9× 45 270
Zhihai Zheng China 10 252 1.5× 221 1.6× 71 1.7× 23 0.9× 30 1.3× 32 292
Dzung Nguyen‐Le Vietnam 9 220 1.3× 199 1.4× 36 0.9× 21 0.8× 27 1.1× 18 268
Shaobo Qiao China 10 312 1.8× 272 2.0× 87 2.1× 30 1.1× 22 0.9× 28 336
Robi Muharsyah Indonesia 9 146 0.9× 163 1.2× 38 0.9× 36 1.3× 11 0.5× 35 246
P. V. Rajesh India 10 277 1.6× 247 1.8× 49 1.2× 35 1.3× 18 0.8× 16 318
Marisol Osman Argentina 10 268 1.6× 216 1.6× 66 1.6× 16 0.6× 15 0.6× 33 307

Countries citing papers authored by Agniv Sengupta

Since Specialization
Citations

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

Fields of papers citing papers by Agniv Sengupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Agniv Sengupta

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

All Works

17 of 17 papers shown
1.
Yang, Yuan, Ming Pan, T. A. Dixon, et al.. (2025). Improving streamflow simulation through machine learning-powered data integration and its potential for forecasting in the Western U.S.. Hydrology and earth system sciences. 29(20). 5453–5476.
2.
Baño‐Medina, Jorge, Agniv Sengupta, James D. Doyle, et al.. (2025). Are AI weather models learning atmospheric physics? A sensitivity analysis of cyclone Xynthia. npj Climate and Atmospheric Science. 8(1). 92–92. 3 indexed citations
3.
Baño‐Medina, Jorge, Agniv Sengupta, Duncan Watson‐Parris, Weihua Hu, & Luca Delle Monache. (2025). Toward Calibrated Ensembles of Neural Weather Model Forecasts. Journal of Advances in Modeling Earth Systems. 17(4). 2 indexed citations
4.
Sengupta, Agniv, Duane E. Waliser, Michael J. DeFlorio, et al.. (2025). Role of evolving sea surface temperature modes of variability in improving seasonal precipitation forecasts. Communications Earth & Environment. 6(1). 256–256.
5.
Yang, Yuan, Dapeng Feng, Hylke E. Beck, et al.. (2025). Global Daily Discharge Estimation Based on Grid Long Short‐Term Memory (LSTM) Model and River Routing. Water Resources Research. 61(6). 2 indexed citations
6.
Monache, Luca Delle, Vesta Afzali Gorooh, Daniel F. Steinhoff, et al.. (2024). Deep Learning of a 200-Member Ensemble with a Limited Historical Training to Improve the Prediction of Extreme Precipitation Events. Monthly Weather Review. 152(7). 1587–1605. 5 indexed citations
7.
DeFlorio, Michael J., Agniv Sengupta, Christopher Castellano, et al.. (2024). Seasonality and climate modes influence the temporal clustering of unique atmospheric rivers in the Western U.S. Communications Earth & Environment. 5(1). 734–734. 2 indexed citations
8.
Hu, Weiming, et al.. (2023). Deep Learning Forecast Uncertainty for Precipitation over the Western United States. Monthly Weather Review. 151(6). 1367–1385. 22 indexed citations
9.
Raymond, Colin, Bin Guan, Huikyo Lee, et al.. (2022). Regional and elevational patterns of extreme heat stress change in the US. Environmental Research Letters. 17(6). 64046–64046. 8 indexed citations
10.
Sengupta, Agniv, Bohar Singh, Michael J. DeFlorio, et al.. (2022). Advances in Subseasonal to Seasonal Prediction Relevant to Water Management in the Western United States. Bulletin of the American Meteorological Society. 103(10). E2168–E2175. 17 indexed citations
11.
Sengupta, Agniv, Duane E. Waliser, Elias Massoud, et al.. (2022). Representation of Atmospheric Water Budget and Uncertainty Quantification of Future Changes in CMIP6 for the Seven U.S. National Climate Assessment Regions. Journal of Climate. 35(22). 7235–7258. 6 indexed citations
12.
Nigam, Sumant, Alfredo Ruiz‐Barradas, & Agniv Sengupta. (2021). The Chennai Water Crisis: Insufficient Rainwater or Suboptimal Harnessing of Runoff?. Current Science. 120(1). 43–43. 2 indexed citations
13.
Wootten, Adrienne, Elias Massoud, Agniv Sengupta, Duane E. Waliser, & Huikyo Lee. (2020). The Effect of Statistical Downscaling on the Weighting of Multi-Model Ensembles of Precipitation. Climate. 8(12). 138–138. 20 indexed citations
14.
Nigam, Sumant & Agniv Sengupta. (2020). The Full Extent of El Niño's Precipitation Influence on the United States and the Americas: The Suboptimality of the Niño 3.4 SST Index. Geophysical Research Letters. 48(3). 21 indexed citations
15.
Massoud, Elias, Bin Guan, Agniv Sengupta, et al.. (2020). Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA). Water. 12(10). 2863–2863. 41 indexed citations
16.
Nigam, Sumant, Agniv Sengupta, & Alfredo Ruiz‐Barradas. (2020). Atlantic–Pacific Links in Observed Multidecadal SST Variability: Is the Atlantic Multidecadal Oscillation’s Phase Reversal Orchestrated by the Pacific Decadal Oscillation?. Journal of Climate. 33(13). 5479–5505. 33 indexed citations
17.
Sengupta, Agniv & Sumant Nigam. (2018). The Northeast Winter Monsoon over the Indian Subcontinent and Southeast Asia: Evolution, Interannual Variability, and Model Simulations. Journal of Climate. 32(1). 231–249. 28 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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