TY - GEN
T1 - On the Impact of Temperature for Precipitation Analysis
AU - Premawardhana, Madara
AU - Azeem, Menatallah Abdel
AU - Sengar, Sandeep Singh
AU - Dev, Soumyabrata
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023/11/21
Y1 - 2023/11/21
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85177855332&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-6702-5_14
DO - 10.1007/978-981-99-6702-5_14
M3 - Conference contribution
AN - SCOPUS:85177855332
SN - 9789819967018
T3 - Smart Innovation, Systems and Technologies
SP - 173
EP - 186
BT - Evolution in Computational Intelligence - Proceedings of the 11th International Conference on Frontiers of Intelligent Computing
A2 - Bhateja, Vikrant
A2 - Yang, Xin-She
A2 - Ferreira, Marta Campos
A2 - Sengar, Sandeep Singh
A2 - Travieso-Gonzalez, Carlos M.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023
Y2 - 11 April 2023 through 12 April 2023
ER -