Climate Informatics: Climate Prediction and Machine Learning

Surabhi Singh

International Journal of Agriculture and Environmental Research, 2025, vol. 11, issue 2

Abstract: One of the important problems in today’s world is climate change, and how can we predict this effectively? Climate informatics is a growing technique/field that combines climate science and data science to understand, model, and predict climate change more effectively. It is evolving because of the combination of data analysis, modern visualization tools, and technically advanced computational skills to manage the complicated and problematic data generated by various climate projects. It has been proved that the deterioration of climate started with the advent of industrialization. Since Machine learning has developed in a bigger way in the last few years, the datasets can be used to be predictive for climate information. In machine learning, machines are trained with data to perform specific tasks and deliver accurate results. Fundamentally, Artificial Intelligence is enabling machine learning to analyze with the help of data that is fed into it. We may have noticed the fluctuations in the climate because of global warming, ozone depletion, and various other reasons, the data obtained from the various sources can be impacted positively or negatively by computer science and machine learning. There are multiple datasets available in the market from different sources, here is the introduction of various types of analysis to interpret the data sets.

Keywords: Environmental; Economics; and; Policy (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ijaeri:356870

DOI: 10.22004/ag.econ.356870

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