Dynamic Mode Decomposition for the Environmental Forecasting Tasks

This paper introduces the dynamic mode decomposition (DMD) for the prediction of the air quality and the precipitation in the presence of high rain as an application of environment prediction tasks by forecasting the appropriate index parameters for each field. The forecasting procedure is based on the use of two real data bases containing the pollutant concentration, and the precipitation for the flooding forecasting. Moreover, the temporal evolution of the DMD modes, can be used to reconstruct the desired components and perform forecasting at the same time using the eigenvalues and eigenvectors. This task of the DMD is already known by the literature, the new in this paper is the application of the DMD for forecasting tasks on the environment issues which present appreciated results that are discussed and well analysed in this paper using different performance indexes to prove its efficiency.