Weather Prediction Algorithm Based on Historical Data Using Kalman Filter

Abstract

This article represents a new method of collection and processing of meteorological data of meteorological service. This operation is based on observations and correction of numerical weather forecast errors by using a new algorithm. This algorithm considerably increases the accuracy of the short-term forecast of external air temperature. The algorithm providing correction of predicted air temperature within the next three hours is considered. Processing of temperature data using Kalman Filter provides the decrease in predicted temperature errors. The work also describes practical use and implementation of accuracy improving algorithm of predicted temperature by using Python.