On the Impact of Temperature for Precipitation Analysis

Climate is the result of the constant interaction between different weather variables where temperature and precipitation are significant factors. Precipitation refers to the condensation of water vapor from clouds as a result of gravitational pull. These variables act as governing factors for determining rainfall, snowfall, and air pressure while determining wide-ranging effects on ecosystems. Different calculation methods could be employed such as Standard Precipitation Index for determining precipitation. Temperature is the measure that is used to identify the heat energy generated by solar radiation and other industrial factors. For understanding the interplay between these two variables, data gathered from several regions of the world including North America, Europe, Australia, and Central Asia was analyzed, and the findings are presented in this paper. Prediction methods such as multiple linear regression and long short-term memory (LSTM) have been employed for predicting rainfall from temperature and precipitation data. The inter-dependency of other weather parameters is also observed in this paper relating to rainfall prediction. The accuracy of the prediction models using machine learning has also been experimented within the study. The implementation of our work is available via https://github.com/MadaraPremawardhana/On-the-Impact-of-Temperature-for-Precipitation-Analysis.