Ashish Dhakate

1.6k total citations
33 papers, 1.2k citations indexed

About

Ashish Dhakate is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Ashish Dhakate has authored 33 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Global and Planetary Change, 31 papers in Atmospheric Science and 16 papers in Oceanography. Recurrent topics in Ashish Dhakate's work include Climate variability and models (32 papers), Meteorological Phenomena and Simulations (28 papers) and Oceanographic and Atmospheric Processes (15 papers). Ashish Dhakate is often cited by papers focused on Climate variability and models (32 papers), Meteorological Phenomena and Simulations (28 papers) and Oceanographic and Atmospheric Processes (15 papers). Ashish Dhakate collaborates with scholars based in India, United Arab Emirates and South Korea. Ashish Dhakate's co-authors include Suryachandra A. Rao, Kiran Salunke, Hemantkumar S. Chaudhari, Subodh Kumar Saha, Samir Pokhrel, C. T. Sabeerali, Somnath Mahapatra, Anupam Hazra, Dandi A. Ramu and B. N. Goswami and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Climatic Change and Quarterly Journal of the Royal Meteorological Society.

In The Last Decade

Ashish Dhakate

31 papers receiving 1.2k citations

Peers

Ashish Dhakate
C. T. Sabeerali India
Lakshmi Krishnamurthy United States
Kiran Salunke India
Prasanth A. Pillai India
Jae-Kyung E. Schemm United States
K. P. Sooraj India
Carsten S. Frederiksen Australia
J. Bader Germany
E. Yulaeva United States
P. Xie United States
C. T. Sabeerali India
Ashish Dhakate
Citations per year, relative to Ashish Dhakate Ashish Dhakate (= 1×) peers C. T. Sabeerali

Countries citing papers authored by Ashish Dhakate

Since Specialization
Citations

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

Fields of papers citing papers by Ashish Dhakate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashish Dhakate

This figure shows the co-authorship network connecting the top 25 collaborators of Ashish Dhakate. A scholar is included among the top collaborators of Ashish Dhakate 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 Ashish Dhakate. Ashish Dhakate 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.
Pillai, Prasanth A., et al.. (2023). Different role of spring season Atlantic SST anomalies in indian summer monsoon rainfall (ISMR) variability before and after early 2000. Climate Dynamics. 61(5-6). 2783–2796. 3 indexed citations
2.
Pillai, Prasanth A. & Ashish Dhakate. (2022). Role of Atlantic SST anomalies in the recent ENSO predictability change in NMME model hindcasts. Climate Dynamics. 59(11-12). 3683–3699.
3.
Dhakate, Ashish & Prasanth A. Pillai. (2022). Seasonal extreme rainfall over Indian monsoon region: a moisture budget analysis to distinguish the role of ENSO and non-ENSO forcing. Theoretical and Applied Climatology. 148(3-4). 1603–1613.
4.
5.
Mukhopadhyay, P., et al.. (2018). Mean and intra‐seasonal variability simulated by NCEP Climate Forecast System model (version 2.0) during boreal winter: Impact of horizontal resolution. International Journal of Climatology. 38(7). 3028–3043. 3 indexed citations
6.
7.
Rao, Suryachandra A., Anupam Hazra, Hemantkumar S. Chaudhari, et al.. (2017). Assessment of simulation of radiation in NCEP Climate Forecasting System (CFS V2). Atmospheric Research. 193. 94–106. 11 indexed citations
8.
Pillai, Prasanth A., Suryachandra A. Rao, Gibies George, et al.. (2016). How distinct are the two flavors of El Niño in retrospective forecasts of Climate Forecast System version 2 (CFSv2)?. Climate Dynamics. 48(11-12). 3829–3854. 26 indexed citations
9.
Saha, Subodh Kumar, Samir Pokhrel, Kiran Salunke, et al.. (2015). Potential predictability of Indian summer monsoon rainfall in NCEP CFSv2. Journal of Advances in Modeling Earth Systems. 8(1). 96–120. 48 indexed citations
10.
Chaudhari, Hemantkumar S., Anupam Hazra, Subodh Kumar Saha, Ashish Dhakate, & Samir Pokhrel. (2015). Indian summer monsoon simulations with CFSv2: a microphysics perspective. Theoretical and Applied Climatology. 125(1-2). 253–269. 14 indexed citations
11.
Pokhrel, Samir, Subodh Kumar Saha, Ashish Dhakate, et al.. (2015). Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error. Climate Dynamics. 46(7-8). 2305–2326. 41 indexed citations
12.
Abhik, S., P. Mukhopadhyay, R. Phani, et al.. (2015). Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system. Climate Dynamics. 46(9-10). 3287–3303. 24 indexed citations
13.
Hazra, Anupam, Hemantkumar S. Chaudhari, Suryachandra A. Rao, et al.. (2015). Impact of revised cloud microphysical scheme in CFSv2 on the simulation of the Indian summer monsoon. International Journal of Climatology. 35(15). 4738–4755. 43 indexed citations
14.
Chattopadhyay, Rajib, R. Phani, C. T. Sabeerali, et al.. (2015). Influence of extratropical sea‐surface temperature on the Indian summer monsoon: an unexplored source of seasonal predictability. Quarterly Journal of the Royal Meteorological Society. 141(692). 2760–2775. 49 indexed citations
15.
Chaudhari, Hemantkumar S., Samir Pokhrel, Subodh Kumar Saha, Ashish Dhakate, & Anupam Hazra. (2014). Improved depiction of Indian summer monsoon in latest high resolution NCEP climate forecast system reanalysis. International Journal of Climatology. 35(10). 3102–3119. 12 indexed citations
16.
Sabeerali, C. T., Suryachandra A. Rao, Ashish Dhakate, Kiran Salunke, & B. N. Goswami. (2014). Why ensemble mean projection of south Asian monsoon rainfall by CMIP5 models is not reliable?. Climate Dynamics. 45(1-2). 161–174. 98 indexed citations
17.
Chaudhari, Hemantkumar S., Samir Pokhrel, Subodh Kumar Saha, et al.. (2012). Model biases in long coupled runs of NCEP CFS in the context of Indian summer monsoon. International Journal of Climatology. 33(5). 1057–1069. 53 indexed citations
18.
Rao, Suryachandra A., Ashish Dhakate, Subodh Kumar Saha, et al.. (2011). Why is Indian Ocean warming consistently?. Climatic Change. 110(3-4). 709–719. 132 indexed citations
19.
Rao, Suryachandra A., Subodh Kumar Saha, Samir Pokhrel, et al.. (2011). Modulation of SST, SSS over northern Bay of Bengal on ISO time scale. Journal of Geophysical Research Atmospheres. 116(C9). 37 indexed citations
20.
Dhakate, Ashish, et al.. (2007). Evolutionary Features of Marine Atmospheric Boundary Layer (MABL) over the Arabian Sea and the Onset of Monsoon over Kerala during ARMEX-2003. Pure and Applied Geophysics. 164(8-9). 1861–1880. 2 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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