Quantum methods for classical meteorology

Abstract

This paper examines the advantages and benefits that quantum computing can offer to methods used in meteorology, focusing on its application to numerical weather prediction (NWP). The paper addresses current challenges and the potential that quantum computing presents for optimizing processes in meteorology, such as ensemble forecasting, quantum machine learning algorithms, and big data processing. Although quantum technology applied to meteorology still faces significant challenges, it offers promising opportunities in critical areas of meteorological prediction and analysis, important in the current context of climate change.
For this reason, a basic implementation of the classical Runge-Kutta method algorithm used for the time integration of differential equations in large-scale meteorological simulations is presented. The classical algorithm is compared with a low-complexity quantum version considering four variables, demonstrating the feasibility of using quantum tools in meteorology.