Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States

Soil organic carbon (SOC) is a key component of the global carbon cycle, yet it is not well-represented in Earth system models to accurately predict global carbon dynamics in response to climate change. This novel study integrated deep learning, data assimilation, 25,444 vertical soil profiles, and...

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Detalles Bibliográficos
Autores principales: Tao, Feng, Zhou, Zhenghu, Huang, Yuanyuan, Li, Qianyu, Lu, Xingjie, Ma, Shuang, Huang, Xiaomeng, Liang, Yishuang, Hugelius, Gustaf, Jiang, Lifen, Doughty, Russell, Ren, Zhehao, Luo, Yiqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Big Data
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931903/
https://www.ncbi.nlm.nih.gov/pubmed/33693391
http://dx.doi.org/10.3389/fdata.2020.00017

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931903/
https://www.ncbi.nlm.nih.gov/pubmed/33693391
http://dx.doi.org/10.3389/fdata.2020.00017

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