TITLE:
Using Python to Predict Global City Temperatures for 400+ Cities
AUTHORS:
Rishi Manjure
KEYWORDS:
Machine Learning, Climate Change, Sustainability, Python, Atmospheric Sciences, Modeling
JOURNAL NAME:
Atmospheric and Climate Sciences,
Vol.13 No.4,
October
31,
2023
ABSTRACT: The purpose of this investigation was to use Python
to model global city temperatures for 400+ cities for many decades. The process
used a compilation of secondary data to find my renowned sources and use
different regression models to plot temperatures. Climate change is an
impending crisis for our Earth, and modeling its changes using Machine Learning
will be crucial to understanding the next steps to combat it. With this model,
researchers can understand which area is most harshly affected by climate
change leading
to prioritization and solutions. They can also figure out the next sustainable
solutions based on climate needs. By using KNeighbors and other regressors, we
can see an increase in temperature worldwide. Although there is some error,
which is inevitable, this is mitigated through several measures. This paper
provides a simple yet critical understanding of how our global temperatures
will increase, based on the last 200+ years.