SIMULATION MODELS BASED ON DIFFERENTIAL EQUATIONS FOR WEATHER FORECASTING

The complexity of atmospheric dynamics poses a significant challenge to meteorologists striving for accurate weather forecasting. This paper explores the application of partial differential equations (PDEs) in simulating atmospheric processes, emphasizing their role in forecasting temperature, pressure, wind velocity, and humidity. We introduce a simplified yet physically consistent 1D simulation framework that draws upon the Navier–Stokes equations, thermodynamic principles, and continuity equations. Numerical solutions are obtained using the finite difference method (FDM) and the Runge-Kutta 4th order scheme. The resulting simulations demonstrate the propagation of thermal and pressure waves in the atmosphere, offering valuable insights into short-term forecasting accuracy. We conclude that differential-equation-based models remain central to weather prediction, especially when coupled with high-resolution data assimilation techniques and parallel computing.