Enhancing climate forecasting with AI: Current state and future prospect [version 1; peer review: awaiting peer review]
Background The escalating impact of climate change underscores the critical need for advanced and sustainable climate forecasting techniques. This review examines the current state and future prospects of leveraging Artificial Intelligence (AI) for climate forecasting, focusing on enhancing accuracy...
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| Published in: | F1000 research Vol. 13; p. 1094 |
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| Main Authors: | , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Background
The escalating impact of climate change underscores the critical need for advanced and sustainable climate forecasting techniques. This review examines the current state and future prospects of leveraging Artificial Intelligence (AI) for climate forecasting, focusing on enhancing accuracy and identifying complex patterns in large datasets.
Methods
A systematic bibliometric methodology was employed, analyzing peer-reviewed literature from the past two decades. The study screened 455 articles from Scopus and Web of Science databases using specific keywords related to AI and weather forecasting. After removing duplicates and irrelevant studies, 218 articles were selected for detailed analysis. Bibliometric analysis was conducted using RStudio software to examine publication trends, co-word co-occurrence, and thematic evolution.
Results
The findings indicate significant growth in AI applications for climate forecasting, particularly from 2014 to 2023. AI techniques such as machine learning, artificial neural networks, and deep learning have shown promise in improving the accuracy of weather forecasts and early warning systems. The thematic analysis identified key themes like numerical weather prediction, feature selection, and neural networks as fundamental areas of research. Additionally, AI-based early warning systems for extreme weather events were highlighted as a crucial application. Below Figure 1. shows the graphical abstract of research
Conclusions
AI has the potential to significantly enhance climate forecasting by analyzing vast amounts of data and identifying complex patterns. Future research should focus on developing universal AI models, increasing model accuracy with explainable AI techniques, and integrating region-specific forecasts to aid decision-making in various sectors. Addressing ethical concerns and ensuring sustainable AI applications are essential for the responsible deployment of AI in climate forecasting. |
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| ISSN: | 2046-1402 2046-1402 |
| DOI: | 10.12688/f1000research.154498.1 |