Exploring the potential of machine learning for simulations of urban ozone variability

Abstract Machine learning (ML) has emerged as a powerful technique in the Earth system science, nevertheless, its potential to model complex atmospheric chemistry remains largely unexplored. Here, we applied ML to simulate the variability in urban ozone (O3) over Doon valley of the Himalaya. The ML...

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Autores principales: Narendra Ojha, Imran Girach, Kiran Sharma, Amit Sharma, Narendra Singh, Sachin S. Gunthe
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/e427481bf236491f82668f22eb027daa
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