Ashis K. Mitra

3.0k total citations
112 papers, 2.1k citations indexed

About

Ashis K. Mitra is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Ashis K. Mitra has authored 112 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Atmospheric Science, 93 papers in Global and Planetary Change and 18 papers in Oceanography. Recurrent topics in Ashis K. Mitra's work include Climate variability and models (91 papers), Meteorological Phenomena and Simulations (83 papers) and Precipitation Measurement and Analysis (46 papers). Ashis K. Mitra is often cited by papers focused on Climate variability and models (91 papers), Meteorological Phenomena and Simulations (83 papers) and Precipitation Measurement and Analysis (46 papers). Ashis K. Mitra collaborates with scholars based in India, United Kingdom and United States. Ashis K. Mitra's co-authors include Satya Prakash, D. S. Pai, Amir AghaKouchak, E. N. Rajagopal, Swati Basu, H. Norouzi, Zhong Liu, Gopal Iyengar, Imran M. Momin and T. N. Krishnamurti and has published in prestigious journals such as Journal of Hydrology, Nature Climate Change and Monthly Weather Review.

In The Last Decade

Ashis K. Mitra

107 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashis K. Mitra India 22 1.8k 1.7k 305 194 191 112 2.1k
Jinzhong Min China 25 1.9k 1.0× 1.7k 1.0× 178 0.6× 100 0.5× 224 1.2× 114 2.1k
E. N. Rajagopal India 20 1.2k 0.7× 1.2k 0.7× 180 0.6× 95 0.5× 154 0.8× 76 1.4k
Mio Matsueda Japan 19 1.6k 0.9× 1.6k 1.0× 89 0.3× 114 0.6× 285 1.5× 45 1.8k
Hann‐Ming Henry Juang United States 23 1.8k 1.0× 1.8k 1.1× 157 0.5× 169 0.9× 224 1.2× 57 2.0k
Zhe Feng United States 30 2.8k 1.6× 2.9k 1.7× 180 0.6× 125 0.6× 222 1.2× 129 3.2k
Lijuan Cao China 18 814 0.5× 1.1k 0.6× 340 1.1× 137 0.7× 72 0.4× 39 1.3k
Peter B. Gibson New Zealand 18 820 0.5× 984 0.6× 143 0.5× 95 0.5× 114 0.6× 43 1.3k
Brian V. Smoliak United States 9 948 0.5× 1.2k 0.7× 128 0.4× 120 0.6× 246 1.3× 11 1.4k
Mei Zhao Australia 16 866 0.5× 1.2k 0.7× 318 1.0× 357 1.8× 292 1.5× 29 1.5k
Ramesh Vellore India 19 938 0.5× 980 0.6× 116 0.4× 63 0.3× 120 0.6× 44 1.2k

Countries citing papers authored by Ashis K. Mitra

Since Specialization
Citations

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

Fields of papers citing papers by Ashis K. Mitra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashis K. Mitra. 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 Ashis K. Mitra. The network helps show where Ashis K. Mitra may publish in the future.

Co-authorship network of co-authors of Ashis K. Mitra

This figure shows the co-authorship network connecting the top 25 collaborators of Ashis K. Mitra. A scholar is included among the top collaborators of Ashis K. Mitra 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 Ashis K. Mitra. Ashis K. Mitra 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.
Kumar, Kondapalli Niranjan, et al.. (2025). Improvements in Precipitation Product with Newer NASA/GPM IMERG Algorithm on TRMM/TMPA Data During Summer Monsoon Period over India. Journal of the Indian Society of Remote Sensing. 53(11). 3917–3934.
2.
Widmann, Martin, et al.. (2024). A comparison of two statistical postprocessing methods for heavy‐precipitation forecasts over India during the summer monsoon. Quarterly Journal of the Royal Meteorological Society. 150(761). 1865–1883. 3 indexed citations
3.
Kumar, Kondapalli Niranjan, Akhilesh Mishra, Raghavendra Ashrit, et al.. (2024). Unraveling Subseasonal Drought Dynamics in India: Insights from NCMRWF Extended Range Prediction System. Journal of Hydrometeorology. 25(8). 1191–1207. 1 indexed citations
4.
Pandey, Avinash C., et al.. (2023). Impact of atmospheric response of ENSO and IOD on boreal summer rainfall variability over the Indian Ocean in coupled models. Climate Dynamics. 61(9-10). 4107–4124. 3 indexed citations
5.
Rani, S. Indira, Gibies George, Sumit Kumar, et al.. (2023). Assimilation of aircraft observations over the Indian monsoon region: Investigation of the effects of COVID‐19 on a reanalysis. Quarterly Journal of the Royal Meteorological Society. 149(752). 894–910. 2 indexed citations
6.
Barton, Emma J., Christopher M. Taylor, Ashis K. Mitra, & A. Jayakumar. (2023). Systematic daytime increases in atmospheric biases linked to dry soils in irrigated areas in Indian operational forecasts. Atmospheric Science Letters. 24(9). 5 indexed citations
7.
Mitra, Ashis K., et al.. (2023). Evaluation of global ocean analysis and forecast system in the Tropical Indian Ocean. Journal of Earth System Science. 132(3). 2 indexed citations
8.
Dube, Anumeha, et al.. (2023). How much does a high-resolution global ensemble forecast improve upon deterministic prediction skill for the Indian summer monsoon?. Meteorology and Atmospheric Physics. 135(4). 3 indexed citations
9.
Jayakumar, A., Kshama Gupta, Saji Mohandas, et al.. (2022). Implementation of the urban parameterization scheme in the Delhi model with an improved urban morphology. Quarterly Journal of the Royal Meteorological Society. 149(750). 40–60. 13 indexed citations
10.
Pattnaik, Sandeep, et al.. (2022). Impacts of sea-surface temperatures on rapid intensification and mature phases of super cyclone Amphan (2020). Journal of Earth System Science. 131(1). 14 indexed citations
11.
Mitra, Ashis K., Sean Milton, Gill Martin, et al.. (2021). Skill of the extended range prediction (NERP) for Indian summer monsoon rainfall with NCMRWF global coupled modelling system. Quarterly Journal of the Royal Meteorological Society. 148(742). 480–498. 5 indexed citations
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14.
Barton, Emma J., Christopher M. Taylor, Douglas J. Parker, et al.. (2019). A case‐study of land–atmosphere coupling during monsoon onset in northern India. Quarterly Journal of the Royal Meteorological Society. 146(731). 2891–2905. 15 indexed citations
15.
Mitra, Ashis K., et al.. (2016). Satellite information of sea ice for model validation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9877. 98772G–98772G. 1 indexed citations
16.
Joshi, P. C., et al.. (2009). Impact of NOAA/TOVS derived moisture profile over the ocean on global data assimilation and medium range weather forecasting. Atmósfera. 15(4). 223–236. 2 indexed citations
17.
Mitra, Ashis K., et al.. (2003). Observed daily large-scale rainfall patterns during BOBMEX-1999. Journal of Earth System Science. 112(2). 223–232. 2 indexed citations
18.
Mitra, Ashis K., et al.. (2001). Impact of satellite derived moisture in a global numerical weather prediction model. Atmósfera. 14(4). 203–209. 6 indexed citations
19.
Biswas, Amal K. & Ashis K. Mitra. (1990). Interspecific hybridization in three species of Sesamum.. Indian Journal of Genetics and Plant Breeding (The). 50(4). 307–309. 7 indexed citations
20.
Mitra, Ashis K., Kanhu Charan Patra, & R. C. Panigrahy. (1990). Seasonal variations of some hydrographical parameters in a tidal creek opening into the Bay of Bengal. Mahasagar. 23(1). 55–62. 20 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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