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Chin. Phys. B, 2025, Vol. 34(7): 070504    DOI: 10.1088/1674-1056/adc7f1
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On the topographic Rossby solitary waves via physical-informed neural networks

Wenxu Liu(刘文绪), Ligeyan Dao(道力格艳), and Ruigang Zhang(张瑞岗)†
School of Mathematical Sciences, Inner Mongolia University, Hohhot 010021, China
Abstract  In the generation and propagation of nonlinear Rossby solitary waves within the atmosphere and ocean, topography occupies a pivotal role. This paper focuses on elucidating the impact of topography on such Rossby solitary waves. Utilizing the perturbation expansion method and spatialtemporal transformations, we derive the Korteweg-de Vries and modified Korteweg-de Vries equation (Gardner equation) governing the amplitude of nonlinear Rossby waves. A fundamental issue addressed herein is a Sturm-Liouville-type ordinary differential equation characterized by variable coefficients and fixed boundary conditions. To numerically solve the derived Korteweg-de Vries and modified Korteweg-de Vries equations, we employ a physical-informed neural network. Both qualitative and quantitative analyses are conducted to discuss the influences of topography and $\beta$ effects, respectively.
Keywords:  Rossby solitary wave      shallow water models      topography      physical-informed neural network  
Received:  02 February 2025      Revised:  26 March 2025      Accepted manuscript online:  02 April 2025
PACS:  05.45.Yv (Solitons)  
  02.30.Mv (Approximations and expansions)  
  47.11.St (Multi-scale methods)  
  92.10.hf (Planetary waves, Rossby waves)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 12462021, 12102205, and 12262025), the Central Guidance for Local Scientific and Technological Development Funding Projects (Grant No. 2024ZY0117), the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region (Grant No. NJYT23098), the Scientific Starting and the Innovative Research Team in the Universities of Inner Mongolia Autonomous Region of China (Grant No. NMGIRT2208), and the National College Students Innovation and Entrepreneurship Training Program (Grant No. 202410126024).
Corresponding Authors:  Ruigang Zhang     E-mail:  rgzhang@imu.edu.cn

Cite this article: 

Wenxu Liu(刘文绪), Ligeyan Dao(道力格艳), and Ruigang Zhang(张瑞岗) On the topographic Rossby solitary waves via physical-informed neural networks 2025 Chin. Phys. B 34 070504

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