Predictive Capacity of Meteorological Data - Will it rain tomorrow

TL;DR

This paper evaluates machine learning models' ability to predict the day of the week from weather data and applies these models to forecast weather conditions across four Australian cities.

Contribution

It introduces a comparative analysis of machine learning techniques for day prediction from weather data and demonstrates their application to weather forecasting.

Findings

Machine learning models can predict the day of the week with reasonable accuracy.

Different cities show varying prediction reliability.

Models can be used to forecast weather conditions based on historical data.

Abstract

With the availability of high precision digital sensors and cheap storage medium, it is not uncommon to find large amounts of data collected on almost all measurable attributes, both in nature and man-made habitats. Weather in particular has been an area of keen interest for researchers to develop more accurate and reliable prediction models. This paper presents a set of experiments which involve the use of prevalent machine learning techniques to build models to predict the day of the week given the weather data for that particular day i.e. temperature, wind, rain etc., and test their reliability across four cities in Australia {Brisbane, Adelaide, Perth, Hobart}. The results provide a comparison of accuracy of these machine learning techniques and their reliability to predict the day of the week by analysing the weather data. We then apply the models to predict weather conditions based on the available data.