M. A. Tolstykh

2.2k total citations
52 papers, 361 citations indexed

About

M. A. Tolstykh is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, M. A. Tolstykh has authored 52 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Atmospheric Science, 34 papers in Global and Planetary Change and 8 papers in Oceanography. Recurrent topics in M. A. Tolstykh's work include Meteorological Phenomena and Simulations (38 papers), Climate variability and models (30 papers) and Atmospheric and Environmental Gas Dynamics (20 papers). M. A. Tolstykh is often cited by papers focused on Meteorological Phenomena and Simulations (38 papers), Climate variability and models (30 papers) and Atmospheric and Environmental Gas Dynamics (20 papers). M. A. Tolstykh collaborates with scholars based in Russia, France and United States. M. A. Tolstykh's co-authors include V. V. Shashkin, D. B. Kiktev, E. M. Volodin, R. B. Zaripov, Alla Yurova, Andrew D. Elvidge, F. Bouyssel, Souhail Boussetta, Simon Vosper and J.‐F. Geleyn and has published in prestigious journals such as Water Resources Research, Journal of Computational Physics and Quarterly Journal of the Royal Meteorological Society.

In The Last Decade

M. A. Tolstykh

46 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. A. Tolstykh Russia 11 318 253 54 48 44 52 361
In‐Hyuk Kwon South Korea 12 464 1.5× 332 1.3× 122 2.3× 14 0.3× 53 1.2× 31 489
Boon S. Chua United States 11 341 1.1× 286 1.1× 294 5.4× 28 0.6× 53 1.2× 17 443
Radmila Brožková Czechia 10 404 1.3× 366 1.4× 102 1.9× 23 0.5× 70 1.6× 18 501
Stuart Fox United Kingdom 12 397 1.2× 323 1.3× 21 0.4× 17 0.4× 30 0.7× 31 433
V. Perov Sweden 6 407 1.3× 350 1.4× 45 0.8× 32 0.7× 152 3.5× 9 459
Alain Caya Canada 12 502 1.6× 315 1.2× 80 1.5× 9 0.2× 65 1.5× 24 529
Motohki Ikawa Japan 9 336 1.1× 271 1.1× 45 0.8× 32 0.7× 37 0.8× 17 371
Slavko Brdar Germany 9 238 0.7× 203 0.8× 12 0.2× 76 1.6× 38 0.9× 13 306
Simon Pellerin Canada 7 538 1.7× 472 1.9× 60 1.1× 27 0.6× 90 2.0× 8 593
Ahoro Adachi Japan 11 282 0.9× 175 0.7× 19 0.4× 24 0.5× 111 2.5× 27 316

Countries citing papers authored by M. A. Tolstykh

Since Specialization
Citations

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

Fields of papers citing papers by M. A. Tolstykh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. A. Tolstykh. 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 M. A. Tolstykh. The network helps show where M. A. Tolstykh may publish in the future.

Co-authorship network of co-authors of M. A. Tolstykh

This figure shows the co-authorship network connecting the top 25 collaborators of M. A. Tolstykh. A scholar is included among the top collaborators of M. A. Tolstykh 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 M. A. Tolstykh. M. A. Tolstykh 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.
Tolstykh, M. A.. (2024). Identifying the Capacity of a Social Network. Moscow University Computational Mathematics and Cybernetics. 48(1). 59–64.
2.
Tolstykh, M. A., et al.. (2024). Improving Performance of SLAV Model for Medium Range Weather Prediction. Lobachevskii Journal of Mathematics. 45(7). 3017–3028.
3.
Tolstykh, M. A.. (2024). Using Numerical Weather Prediction Models for Climate Modeling. Izvestiya Atmospheric and Oceanic Physics. 60(S1). S139–S143.
4.
Tolstykh, M. A., et al.. (2024). The SLAV072L96 Model for Long-range Meteorological Forecasts. Russian Meteorology and Hydrology. 49(7). 576–586. 3 indexed citations
5.
Solomon, Amy, Matthew D. Shupe, Gunilla Svensson, et al.. (2023). The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign. Elementa Science of the Anthropocene. 11(1). 21 indexed citations
6.
Saurral, Ramiro I., William J. Merryfield, M. A. Tolstykh, et al.. (2021). A Data Set for Intercomparing the Transient Behavior of Dynamical Model‐Based Subseasonal to Decadal Climate Predictions. Journal of Advances in Modeling Earth Systems. 13(9). 4 indexed citations
7.
8.
Tolstykh, M. A., et al.. (2021). Development of the global multiscale atmosphere model: computational aspects. Journal of Physics Conference Series. 1740(1). 12074–12074. 1 indexed citations
9.
Tolstykh, M. A., et al.. (2020). Verification of heavy precipitation forecasts of the SL-AV20 global operational atmosphere model. 96–112. 3 indexed citations
10.
Elvidge, Andrew D., Irina Sandu, Nils Wedi, et al.. (2019). Uncertainty in the Representation of Orography in Weather and Climate Models and Implications for Parameterized Drag. Journal of Advances in Modeling Earth Systems. 11(8). 2567–2585. 32 indexed citations
11.
Tolstykh, M. A., et al.. (2019). Development of SL-AV global semi-Lagrangian atmosphere model in 2009–2019. 4. 77–91. 4 indexed citations
12.
Shashkin, V. V., M. A. Tolstykh, & E. M. Volodin. (2019). Stratospheric Circulation Modeling with the SL-AV Semi-Lagrangian Atmospheric Model. Russian Meteorology and Hydrology. 44(1). 1–12. 3 indexed citations
13.
Tolstykh, M. A., et al.. (2019). Climate Version of the SL-AV Global Atmospheric Model: Development and Preliminary Results. Russian Meteorology and Hydrology. 44(1). 13–22. 10 indexed citations
14.
Tolstykh, M. A., et al.. (2018). Structure and Algorithms of SL-AV Atmosphere Model Parallel Program Complex. Lobachevskii Journal of Mathematics. 39(4). 587–595. 6 indexed citations
15.
Tolstykh, M. A., et al.. (2018). Design and development of the SLAV-INMIO-CICE coupled model for seasonal prediction and climate research. Russian Journal of Numerical Analysis and Mathematical Modelling. 33(6). 333–340. 5 indexed citations
16.
Tolstykh, M. A., et al.. (2017). Vorticity-divergence semi-Lagrangian global atmospheric model SL-AV20: dynamical core. Geoscientific model development. 10(5). 1961–1983. 24 indexed citations
17.
Yurova, Alla, M. A. Tolstykh, Mats B. Nilsson, & Andrey Sirin. (2014). Parameterization of mires in a numerical weather prediction model. Water Resources Research. 50(11). 8982–8996. 5 indexed citations
18.
Shashkin, V. V. & M. A. Tolstykh. (2014). Inherently mass-conservative version of the semi-Lagrangian absolute vorticity (SL-AV) atmospheric model dynamical core. Geoscientific model development. 7(1). 407–417. 5 indexed citations
19.
Tolstykh, M. A.. (1996). Global semi-Lagrangian atmospheric model based on compact finite-differences. 1 indexed citations
20.
Tolstykh, M. A.. (1994). Application of Fifth-Order Compact Upwind Differencing to Moisture Transport Equation in Atmosphere. Journal of Computational Physics. 112(2). 394–403. 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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