Ananda Das

807 total citations
48 papers, 552 citations indexed

About

Ananda Das is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Ananda Das has authored 48 papers receiving a total of 552 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Atmospheric Science, 22 papers in Global and Planetary Change and 11 papers in Oceanography. Recurrent topics in Ananda Das's work include Meteorological Phenomena and Simulations (22 papers), Tropical and Extratropical Cyclones Research (19 papers) and Climate variability and models (18 papers). Ananda Das is often cited by papers focused on Meteorological Phenomena and Simulations (22 papers), Tropical and Extratropical Cyclones Research (19 papers) and Climate variability and models (18 papers). Ananda Das collaborates with scholars based in India, United States and Japan. Ananda Das's co-authors include Wounjhang Park, S. K. Roy Bhowmik, Suehyun Cho, Kyoungsik Kim, Chenchen Mao, Krishna K. Osuri, U. C. Mohanty, Raghu Nadimpalli, Kyuyoung Bae and Dev Niyogi and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Applied Physics.

In The Last Decade

Ananda Das

45 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ananda Das India 11 273 218 173 89 84 48 552
Yuefeng Li China 12 155 0.6× 138 0.6× 156 0.9× 48 0.5× 112 1.3× 50 447
H. Kanamori Japan 16 223 0.8× 233 1.1× 226 1.3× 45 0.5× 144 1.7× 53 749
Keguang Wang Norway 14 377 1.4× 193 0.9× 109 0.6× 60 0.7× 16 0.2× 30 711
Song Yang China 15 388 1.4× 388 1.8× 400 2.3× 147 1.7× 289 3.4× 36 1.1k
Mi‐Hee Ji United States 17 178 0.7× 200 0.9× 270 1.6× 99 1.1× 190 2.3× 42 790
Yujie Wu China 16 135 0.5× 146 0.7× 410 2.4× 81 0.9× 70 0.8× 43 668
Tetsuya Kawano Japan 14 275 1.0× 268 1.2× 96 0.6× 66 0.7× 48 0.6× 52 480
N.S.M.P. Latha Devi India 11 64 0.2× 54 0.2× 160 0.9× 36 0.4× 107 1.3× 30 459
Yipeng Guo China 19 590 2.2× 675 3.1× 218 1.3× 366 4.1× 68 0.8× 59 1.0k
Jisk Attema Netherlands 15 230 0.8× 259 1.2× 157 0.9× 16 0.2× 46 0.5× 38 627

Countries citing papers authored by Ananda Das

Since Specialization
Citations

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

Fields of papers citing papers by Ananda Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ananda Das

This figure shows the co-authorship network connecting the top 25 collaborators of Ananda Das. A scholar is included among the top collaborators of Ananda Das 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 Ananda Das. Ananda Das 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.
Raychaudhuri, Barun, et al.. (2025). Climate forcing due to atmospheric water vapour over the tropical regions of India. Advances in Space Research. 76(6). 3275–3290.
2.
Srivastava, Akhil, M. Mohapatra, Ananda Das, Raghu Nadimpalli, & Suneet Dwivedi. (2023). A new approach to generate dynamical cone of uncertainty for cyclone track forecast over North Indian Ocean. Natural Hazards. 120(4). 3467–3485.
3.
Nadimpalli, Raghu, et al.. (2023). Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region. SHILAP Revista de lepidopterología. 3(1). 8 indexed citations
4.
Sahany, Sandeep, et al.. (2023). Recent changes in the climatological characteristics of daily contiguous rain areas over India. npj Climate and Atmospheric Science. 6(1). 2 indexed citations
5.
Osuri, Krishna K., et al.. (2022). Numerical modeling of tropical cyclone size over the Bay of Bengal: influence of microphysical processes and horizontal resolution. Meteorology and Atmospheric Physics. 134(4). 11 indexed citations
6.
Mohanty, Shyama, Raghu Nadimpalli, Sudheer Joseph, et al.. (2022). Influence of the ocean on tropical cyclone intensity using a high resolution coupled atmosphere–ocean model: A case study of very severe cyclonic storm Ockhi over the North Indian Ocean. Quarterly Journal of the Royal Meteorological Society. 148(746). 2282–2298. 3 indexed citations
7.
Osuri, Krishna K., et al.. (2022). Understanding the characteristics of microphysical processes in the rapid intensity changes of tropical cyclones over the Bay of Bengal. Quarterly Journal of the Royal Meteorological Society. 148(749). 3715–3729. 6 indexed citations
8.
Srivastava, Akhil, V. S. Prasad, Ananda Das, & Arun Kumar Sharma. (2021). A HWRF-POM-TC coupled model forecast performance over North Indian Ocean: VSCS TITLI & VSCS LUBAN. 10(1). 54–70. 6 indexed citations
9.
Nadimpalli, Raghu, Akhil Srivastava, V. S. Prasad, et al.. (2020). Impact of INSAT-3D/3DR Radiance Data Assimilation in Predicting Tropical Cyclone Titli Over the Bay of Bengal. IEEE Transactions on Geoscience and Remote Sensing. 58(10). 6945–6957. 22 indexed citations
10.
Jaman, Mohammad Firoj, et al.. (2020). A new country record of Smooth-backed Gliding Gecko Gekko lionotum (Annandale, 1905) (Squamata: Gekkonidae) from Bangladesh. Journal of Threatened Taxa. 12(15). 17161–17164.
11.
Das, Ananda, Chenchen Mao, Suehyun Cho, Kyoungsik Kim, & Wounjhang Park. (2018). Over 1000-fold enhancement of upconversion luminescence using water-dispersible metal-insulator-metal nanostructures. Nature Communications. 9(1). 4828–4828. 118 indexed citations
12.
Das, Ananda, et al.. (2016). Verification of real-time WRF-ARW forecast in IMD during monsoon 2010. MAUSAM. 67(2). 333–356. 2 indexed citations
13.
Das, Ananda, et al.. (2014). Vefrifikacija prognoza oborine WRF modelom nad Indijom tijekom monsuna 2010.: CRA metoda. Geofizika. 31(2). 106–126. 1 indexed citations
14.
Bhowmik, S. K. Roy, et al.. (2012). Implementation of Polar WRF for short range prediction of weather over Maitri region in Antarctica. Journal of Earth System Science. 121(5). 1125–1143. 6 indexed citations
15.
Das, Ananda, et al.. (2010). Evidence of Lath Martensite in High-C Japanese Sword Produced from Tamahagane Steel by Tatara Process. Materials science forum. 654-656. 138–141. 4 indexed citations
16.
Das, Ananda, et al.. (2006). New Ternary Ordered Structures in CuMPt6(M = 3d elements) Alloys. Journal of the Physical Society of Japan. 75(2). 24604–24604. 7 indexed citations
17.
Das, Ananda, et al.. (2005). Radijus utjecaja oborine nad područjem monsuna u Indiji. Geofizika. 22(1). 131–141. 2 indexed citations
18.
Routray, Ashish, et al.. (2005). Study of heavy rainfall event over West Coast of India using analysis nudging in MM5 during ARMEX-I. MAUSAM. 56(1). 107–120. 31 indexed citations
19.
Bhowmik, S. K. Roy, et al.. (2005). Radius of rainfall influence over Indian monsoon region. 3 indexed citations
20.
Das, Ananda, et al.. (2003). Circulation characteristics of a monsoon depression during BOBMEX-99 using high-resolution analysis. Journal of Earth System Science. 112(2). 165–184. 6 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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