Kameswarrao Modali

3.2k total citations
9 papers, 89 citations indexed

About

Kameswarrao Modali is a scholar working on Atmospheric Science, Global and Planetary Change and Computer Networks and Communications. According to data from OpenAlex, Kameswarrao Modali has authored 9 papers receiving a total of 89 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Atmospheric Science, 6 papers in Global and Planetary Change and 1 paper in Computer Networks and Communications. Recurrent topics in Kameswarrao Modali's work include Climate variability and models (6 papers), Meteorological Phenomena and Simulations (4 papers) and Cryospheric studies and observations (2 papers). Kameswarrao Modali is often cited by papers focused on Climate variability and models (6 papers), Meteorological Phenomena and Simulations (4 papers) and Cryospheric studies and observations (2 papers). Kameswarrao Modali collaborates with scholars based in Germany, Italy and United Kingdom. Kameswarrao Modali's co-authors include Holger Pohlmann, Wolfgang A. Müller, Jochem Marotzke, Klaus Pankatz, Johanna Baehr, Sebastian Hettrich, Matthias Bittner, Armin Köhl, Freja Vamborg and Barbara Früh and has published in prestigious journals such as Scientific Reports, Geophysical Research Letters and Climate Dynamics.

In The Last Decade

Kameswarrao Modali

8 papers receiving 88 citations

Peers

Kameswarrao Modali

GPC

AS

OCEAN

WST

EEBS

Klaus Pankatz Germany

M. C. Pinheiro United States

Karl‐Hermann Wieners Germany

Russell Glazer Italy

Roseanna C. McKay Australia

Martin Bergemann Australia

Alasdair Hunter United Kingdom

Tzu‐Ting Lo Taiwan

Balakrishnan Solaraju-Murali Spain

Xavier Yepes-Arbós Spain

Klaus Pankatz Germany

Kameswarrao Modali

99 ×1.3

GPC

91 ×1.3

AS

24 ×1.7

OCEAN

8 ×1.3

WST

5 ×1.3

EEBS

Citations per year, relative to Kameswarrao Modali Kameswarrao Modali (= 1×) peers Klaus Pankatz

Countries citing papers authored by Kameswarrao Modali

Since Specialization

Citations

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

Fields of papers citing papers by Kameswarrao Modali

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kameswarrao Modali

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Zanchettin, Davide, Kameswarrao Modali, Wolfgang A. Müller, & Angelo Rubino. (2024). Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR. Atmosphere. 15(3). 295–295. 1 indexed citations

2.

Prims, Oriol Tintó, Robert Redl, Marc Rautenhaus, et al.. (2024). The effect of lossy compression of numerical weather prediction data on data analysis: a case study using enstools-compression 2023.11. Geoscientific model development. 17(24). 8909–8925.

3.

Meyer, Marcel, et al.. (2021). Interactive 3-D visual analysis of ERA5 data: improving diagnostic indices for marine cold air outbreaks and polar lows. Weather and Climate Dynamics. 2(3). 867–891. 10 indexed citations

4.

Reyers, Mark, Hendrik Feldmann, Sebastian Mieruch, et al.. (2019). Development and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependency. Earth System Dynamics. 10(1). 171–187. 8 indexed citations

5.

Pohlmann, Holger, Wolfgang A. Müller, Matthias Bittner, et al.. (2019). Realistic Quasi‐Biennial Oscillation Variability in Historical and Decadal Hindcast Simulations Using CMIP6 Forcing. Geophysical Research Letters. 46(23). 14118–14125. 26 indexed citations

6.

Paxian, Andreas, Markus Ziese, Frank Kreienkamp, et al.. (2018). User-oriented global predictions of the GPCC drought index for the next decade. Meteorologische Zeitschrift. 28(1). 3–21. 12 indexed citations

7.

Zanchettin, Davide, Carlo Gaetan, Kameswarrao Modali, et al.. (2017). Structural decomposition of decadal climate prediction errors: A Bayesian approach. Scientific Reports. 7(1). 12862–12862. 4 indexed citations

8.

Kröger, Jürgen, Holger Pohlmann, Frank Sienz, et al.. (2017). Full-field initialized decadal predictions with the MPI earth system model: an initial shock in the North Atlantic. Climate Dynamics. 51(7-8). 2593–2608. 27 indexed citations

9.

Modali, Kameswarrao, et al.. (2013). Climate Data Operators for quick look visualization. EGU General Assembly Conference Abstracts. 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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