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

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 (O(3)) over Doon valley of the Himalaya. The ML model,...

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Detalles Bibliográficos
Autores principales: Ojha, Narendra, Girach, Imran, Sharma, Kiran, Sharma, Amit, Singh, Narendra, Gunthe, Sachin S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602617/
https://www.ncbi.nlm.nih.gov/pubmed/34795336
http://dx.doi.org/10.1038/s41598-021-01824-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602617/
https://www.ncbi.nlm.nih.gov/pubmed/34795336
http://dx.doi.org/10.1038/s41598-021-01824-z

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