Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Sergey Kravtsov"'
Autor:
Sergey Kravtsov, Anastasios A. Tsonis
Publikováno v:
Entropy, Vol 23, Iss 8, p 951 (2021)
Dynamical systems like the one described by the three-variable Lorenz-63 model may serve as metaphors for complex natural systems such as climate systems. When these systems are perturbed by external forcing factors, they tend to relax back to their
Externí odkaz:
https://doaj.org/article/15e1af22bf1949aeba4232a291a9f485
Autor:
Anastasios A. Tsonis, Geli Wang, Wenxu Lu, Sergey Kravtsov, Christopher Essex, Michael W. Asten
Publikováno v:
Entropy, Vol 23, Iss 4, p 459 (2021)
Proxy temperature data records featuring local time series, regional averages from areas all around the globe, as well as global averages, are analyzed using the Slow Feature Analysis (SFA) method. As explained in the paper, SFA is much more effectiv
Externí odkaz:
https://doaj.org/article/7a22709bd8b549f39c46f6e8084122af
Publikováno v:
Water, Vol 6, Iss 8, Pp 2278-2299 (2014)
This study disentangles causes of the Michigan-Huron system lake-level variability. Regional precipitation is identified as the primary driver of lake levels with sub-monthly time lag, implying that the lake-level time series can be used as a proxy f
Externí odkaz:
https://doaj.org/article/f626721a58a34c379e8a2f1ee2552c7d
Publikováno v:
Weather and Forecasting.
This study introduces a novel method for comparing vertical thermodynamic profiles, focusing on the atmospheric boundary layer, across a wide range of meteorological conditions. This method is developed using observed temperature and dewpoint tempera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd7b57231cffc1fa0c4eccbdd369a498
https://doi.org/10.1175/waf-d-22-0195.1
https://doi.org/10.1175/waf-d-22-0195.1
Autor:
Andrey Gavrilov, Sergey Kravtsov, Maria Buyanova, Dmitry Mukhin, Evgeny Loskutov, Alexander Feigin
Estimating climate response to observed and projected increases in atmospheric greenhouse gases usually requires averaging among multiple independent simulations of computationally expensive global climate models to filter out the spontaneous interna
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edd566d12ecf7746831ba75f2dc5f596
https://doi.org/10.21203/rs.3.rs-2715545/v1
https://doi.org/10.21203/rs.3.rs-2715545/v1
Publikováno v:
Weather and Forecasting. 37:727-748
This paper utilizes statistical and statistical–dynamical methodologies to select, from the full observational record, a minimal subset of dates that would provide representative sampling of local precipitation distributions across the contiguous U
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5e6d5208e79f6d49c6c2d2bdd2607c7
https://doi.org/10.1175/waf-d-21-0162.1
https://doi.org/10.1175/waf-d-21-0162.1
Autor:
Sergey Kravtsov, Anna Prokhorova
Publikováno v:
The Humanities and Social Sciences. 84:61-72
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2ca5476b910588ab297f5865d296a29
https://doi.org/10.18522/2070-1403-2021-84-1-61-72
https://doi.org/10.18522/2070-1403-2021-84-1-61-72
This paper contains a description of recent changes to the formulation and numerical implementation of the Quasi-Geostrophic Coupled Model (Q-GCM), which constitute a major update of the previous version of the model (Hogg et al., 2014). The Q-GCM mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f9da891934702f7651de4297a45f96e
https://gmd.copernicus.org/articles/15/7449/2022/
https://gmd.copernicus.org/articles/15/7449/2022/
Autor:
Sergey Kravtsov, Tatiana Simonyan
Publikováno v:
KANT. 37:201-205
The article is devoted to the study of foreign and domestic experience in improving the efficiency of public-private partnerships in the field of air transportation. The authors analyze the methods and tools of cooperation in the field of PPP and com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75b9e8739d397537ee468b65541c3d3e
https://doi.org/10.24923/2222-243x.2020-37.43
https://doi.org/10.24923/2222-243x.2020-37.43