0561775 20230418205119.220221003235959.9 85113387774 000688431300002 10.1007/s10959-021-01125-1 46 s. P cav_un_epca*02540800894-9840353 (2022)1736-1781Springer large deviations principle moderate deviations principle primitive equations weak convergence approach cav_un_auth*0370372 Slavík Jakub UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2022/SI/slavik-0561775.pdf https://link.springer.com/article/10.1007/s10959-021-01125-1 We establish the large deviations principle (LDP) and the moderate deviations principle (MDP) and an almost sure version of the central limit theorem (CLT) for the stochastic 3D viscous primitive equations driven by a multiplicative white noise allowing dependence on spatial gradient of solutions with initial data in H2. The LDP is established using the weak convergence approach of Budjihara and Dupuis and uniform version of the stochastic Gronwall lemma. The result corrects a minor technical issue in Z. Dong, J. Zhai, and R. Zhang: Large deviations principles for 3D stochastic primitive equations, J. Differential Equations, 263(5):3110–3146, 2017, and establishes the result for a more general noise. The MDP is established using a similar argument. WOS BA 10000 10100 10103 2023 1 RVO:67985556 https://hdl.handle.net/11104/0335180 S Article Statistics Probability C STATISTICS&PROBABILITY 0.7 0.1 10.5 0.00273 0.625 1136 0.659 0.700 83 Q4 16.4 Q3 Q2 0.34 Q4 16.4 2022 85113387774 SCOPUS PUBMED 000688431300002 WOS cav_un_epca*0254080 Journal of Theoretical Probability 0894-9840 1572-9230 Roč. 35 č. 3 2022 1736 1781 Springer