Публикации

Gritsun, Andrey S., Volodin, Evgeny M., Bragina, Vasilisa V. and Tarasevich, Maria A.. «Simulation of modern and future climate by INM-CM6M» Russian Journal of Numerical Analysis and Mathematical Modelling 39, no. 6 (2024): 329-341. https://doi.org/10.1515/rnam-2024-0028

Volodin E. M., Blagodatskih D. V., Bragina V. V. et al. Computational framework for the Earth system modelling and the INM-CM6 climate model implemented on its base. — Russ. J. Numercal Analysis Math. Modelling 39, no. 6 (2024): 379—392. https://doi.org/10.1515/rnam-2024-0032

Tarasevich, M. A., Tsybulin, I. V., Volodin, E. M., & Gritsun, A. S. (2024). Analysis and Optimization of Output Operations in the INM RAS Earth System Model. Supercomputing Frontiers and Innovations10(4), 46-61. https://doi.org/10.14529/jsfi230405

Chernenkov, Alexey Yu., Volodin, Evgeny M. and Stepanenko, Victor M.. «Nitrogen cycle module for INM RAS climate model» Russian Journal of Numerical Analysis and Mathematical Modelling, vol. 39, no. 4, 2024, pp. 187-197. https://doi.org/10.1515/rnam-2024-0018

Bragina (Vorobyeva) V. V., Tarasevich M. A., and Volodin E. M. Prediction of the Arctic Sea Ice Characteristics for Summer Seasons using the INM RAS Earth System Model, Russian Meteorology and Hydrology, 2024, Vol. 49, No. 8, pp. 681–690.

Vargin, P.N., Bragina, V.V., Volodin, E.M. et al. Investigation of the Predictability of the Arctic Stratospheric Polar Vortex Variability in the INMCM5 Seasonal Predictions. Russ. Meteorol. Hydrol. 49, 700–710 (2024). https://doi.org/10.3103/S1068373924080053

Aleksandrov, M.S., Volodin, E.M. & Vorobyeva, V.V. Study of the PDO Index Predictability for 1 to 5 Years with INMCM5. Oceanology 64, 731–736 (2024). https://doi.org/10.1134/S0001437024700401

Chernenkov A. Y. and Volodin E. M., “New land use parameterization for INM-CM terrestrial carbon cycle module,” Numerical Methods and Programming 25, no. 3 (2024): 315–325, https://doi.org/10.26089/NumMet.v25r324

Bragina V., Volodin E., Chernenkov A. et al. Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model. — Clim. Dyn., 2024, vol. 62, pp. 7783—7797.

Chernenkov A., Volodin E., Kostrykin S., Tarasevich M., Vorobyeva V. Modification and Validation of the Soil–Snow Module in the INM RAS Climate Model. — Atmosphere, 2024, vol. 15(4), 422.

Resnyanskii, Y.D., Zelen’ko, A.A., Strukov, B.S. et al. Assessment of the Reproducibility of Oceanographic Fields in Retrospective Forecasts Using the INM-CM5 Earth System Model. Russ. Meteorol. Hydrol. 49, 183–194 (2024). https://doi.org/10.3103/S1068373924030014

Makosko, A.A., Matesheva, A.V. & Emelina, S.V. On Trends in the Health Risks from Air Pollution and in Changing Levels of Weather and Climate Comfort in Russia until 2050. Russ. Meteorol. Hydrol. 49, 158–167 (2024). https://doi.org/10.3103/S1068373924020092

Хан В. М., Круглова Е. Н., Тищенко В. А., Куликова И. А., Субботин А. В., Грицун А. С., Володин Е. М., Тарасевич М. А., Брагина (Воробьева) В. В. Верификация сезонных ансамблевых прогнозов на базе модели земной системы INM-CM5 // Метеорология и гидрология. — 2024. — № 7.— С. 40–56.

Blagodatskikh D. V. Comparison of computational efficiency of two versions of a terrain-following ocean climate model — Numerical Methods and Programming, 2023, vol. 24,  no. 4, pp. 440—449.

Blagodatskikh D. V., Iakovlev N. G. et al. Non-local discretization of the isoneutral diffusion operator in a terrain-following climate ocean model, Russian Journal of Numerical Analysis and Mathematical Modelling, 2023, vol. 38, no. 6, pp. 1—8.

Tarasevich M, Tsybulin I, Onoprienko V, Kulyamin D, Volodin E. Ensemble-based statistical verification of INM RAS Earth system model. Russian Journal of Numerical Analysis and Mathematical Modelling. 2023;38(3): 173-186. https://doi.org/10.1515/rnam-2023-0014

Tarasevich, M., Sakhno, A., Blagodatskikh, D., Fadeev, R., Volodin, E., Gritsun, A. (2023). Scalability of the INM RAS Earth System Model. In: Voevodin, V., Sobolev, S., Yakobovskiy, M., Shagaliev, R. (eds) Supercomputing. RuSCDays 2023. Lecture Notes in Computer Science, vol 14388. Springer, Cham. https://doi.org/10.1007/978-3-031-49432-1_16

Vilfand, R.M., Kulikova, I.A., Khan, V.M. et al. Analysis of Intraseasonal Variability and Predictability of Regional-Scale Atmospheric Processes at Midlatitudes of the Northern Hemisphere. Izv. Atmos. Ocean. Phys. 59, 457–469 (2023). https://doi.org/10.1134/S0001433823050110

Vorobeva, V.V., Volodin, E.M., Gritsun, A.S. et al. Analysis of the Atmosphere and the Ocean Upper Layer State Predictability for up to 5 Years Ahead Using the INMCM5 Climate Model Hindcasts. Russ. Meteorol. Hydrol. 48, 581–589 (2023). https://doi.org/10.3103/S106837392307004X

Khan, V.M., Vil’fand, R.M., Tishchenko, V.A. et al. Assessment of Changes in the Temperature Regime of Northern Eurasia for the Next Five Years According to the INM RAS Earth System Model Forecasts and Their Possible Consequences for Agriculture. Russ. Meteorol. Hydrol. 48, 745–754 (2023). https://doi.org/10.3103/S1068373923090029

Sumerova, K.A., Vargin, P.N., Lukyanov, A.N. et al. Analysis of Tropospheric and Stratospheric Circulation Conditions That Contributed to the Formation of Cold Waves in the Northwest and Center of European Russia in December 2021. Russ. Meteorol. Hydrol. 48, 931–945 (2023). https://doi.org/10.3103/S106837392311002X

Kulikova, I.A., Nabokova, E.V., Khan, V.M. et al. Madden–Julian Oscillation in the Context of Subseasonal Variability, Teleconnections, and Predictability. Russ. Meteorol. Hydrol. 48, 645–657 (2023). https://doi.org/10.3103/S1068373923080010

Semenova, N.K., Simonov, Y.A. & Khristoforov, A.V. Extended Streamflow Prediction for Russian Rivers. Russ. Meteorol. Hydrol. 48, 1019–1028 (2023). https://doi.org/10.3103/S1068373923120026

Borshch, S.V., Kolii, V.M., Ryseva, E.A. et al. Methodology for Calculating Daily Streamflow of Russian Rivers Using the HBV-96 Runoff Formation Model. Russ. Meteorol. Hydrol. 48, 221–228 (2023). https://doi.org/10.3103/S1068373923030044

Варенцов А.И., Имеев О.А., Глазунов А.В., Мортиков Е.В., Степаненко В.М. Численное моделирование переноса твёрдых частиц в атмосферном городском пограничном слое с использованием лагранжева подхода: физические задачи и параллельная реализация. // Труды ИСП РАН. — 2023. — Т. 35, № 4.— С. 145–164. DOI: 10.15514/ISPRAS–2023–35(4)–8.

Суязова В. И., Дебольский А. В., Мортиков Е. В. Исследование характеристик приземного слоя при наличии взвешенных снежных частиц с помощью данных наблюдений и вихреразрешающего моделирования // Известия Российской академии наук. Физика атмосферы и океана. — 2024.

Evtushenko, A.; Svechnikova, E.; Kudryavtsev, A., Analysis of Sprite Activity in Middle Latitudes. Atmosphere 2024, 15, 169. https://doi.org/10.3390/atmos15020169

Gladskikh D., Mortikov E., Ahtamyanov R. On the parameterization of aerodynamic roughness in numerical modeling of the land water bodies // Proceedings of the 9th International Conference on Physical and Mathematical Modelling of Earth and Environmental Processes. — VDI-PLATZ 1, DUSSELDORF,GERMANY, D-40468: SPRINGER-V D I VERLAG GMBH & CO KG, 2023.

Imanova, A.S., Smyshlyaev, S.P., Rozanov, E.V. (2023). Analysis of Factors Affecting the Interannual Variability of Antarctic Ozone. In: Kosterov, A., Lyskova, E., Mironova, I., Apatenkov, S., Baranov, S. (eds) Problems of Geocosmos—2022. ICS 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-40728-4_3

Jakovlev, A.R.; Smyshlyaev, S.P. The Impact of the Tropical Sea Surface Temperature Variability on the Dynamical Processes and Ozone Layer in the Arctic Atmosphere. Meteorology 20243, 36-69. https://doi.org/10.3390/meteorology3010002

Kadantsev, E., Mortikov, E., Glazunov, A., Kleeorin, N., и Rogachevskii, I. On dissipation time scales of the basic second-order moments: the effect on the Energy and Flux-Budget (EFB) turbulence closure for stably stratified turbulence // Nonlinear processes in geophysics, EGUsphere, 2024, 1–20, preprint 10.5194/egusphere-2023-3164

Murzina S et al. Comparative Analysis of the Fatty Acid Profiles of Antarctic Krill (Euphausia superba Dana, 1850) in the Atlantic Sector of the Southern Ocean: Certain Fatty Acids Reflect the Oceanographic and Trophic Conditions of the Habitat // J. Marine Science and Engineering V.11, iss 10, 10.3390/jmse11101912. (https://www.mdpi.com/2077-1312/11/10/1912).

Nerobelov, G.; Timofeyev, Y.; Foka, S.; Smyshlyaev, S.; Poberovskiy, A.; Sedeeva, M. Complex Validation of Weather Research and Forecasting—Chemistry Modelling of Atmospheric CO2 in the Coastal Cities of the Gulf of Finland. Remote Sens. 202315, 5757. https://doi.org/10.3390/rs15245757

Seleznev A., Gavrilov A., Mukhin D., Gritsun A., Volodin E., ENSO phase locking, asymmetry and predictability in the INM RAS Earth system model // Russian Journal of Numerical Analysis and Mathematical Modelling 2024,Vol. 39.,N. 1., P. 35–46. DOI: 10.1515/rnam-2024-0004.

Smyshlyaev, S.; Jakovlev, A.R.; Galin, V.Y. Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability. Preprints 2024, 2024010050. https://doi.org/10.20944/preprints202401.0050.v1

Varentsov A. I., Imeev O. A., Glazunov A. V. et al. Numerical simulation of particulate matter transport in the atmospheric urban boundary layer using the lagrangian approach: Physical problems and parallel implementation // Programming and Computer Software. — 2023. — Vol. 49, no. 8. — P. 894–905.