Temperature prediction based on XGBoost-PredRNN++

Abstract

The life of most industrial instruments is closely related to the local climate, and there is a significant correlation between the development of industry and the local climate. In order to explore the future global temperature distribution pattern and temperature level under the global warming trend, the global temperature data published in Worldclim is used. The XGBoost-RedRNN++ model is proposed in this paper to forecast the future temperature, and the regional global temperature prediction is carried out with 5 'as the precision unit. After predicting global average temperature of 20.78 centigrade in 2050 and 22.54 centigrade in 2100. The similarity of the global average temperature distribution in 2050 and the average temperature distribution in 2021 is 95.54%, and the similarity of the global average temperature distribution in 2100 compared with 2021 is 81.21%. With time going on, the temperature is generally rising everywhere. The global lowest temperature in 2050 and 2100 will be in Antarctica, with an average annual temperature of -14.6 centigrade and -12.4 centigrade. The highest global temperature in 2050 and 2100 will occur in Central Africa, with an average annual temperature of 85.2 centigrade and 87.5 centigrade. Additionally, it was observed that the temperature gradually decreased from the equator to the poles, and the land temperature in the southern hemisphere was significantly higher than that in the northern hemisphere. This study can not only lay the foundation for the future industrial development, but also provide theoretical support for the reform direction of the national industrial constitution.