Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 5
Articles | Volume 15, issue 5
https://doi.org/10.5194/gmd-15-1899-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-1899-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 5
Model description paper
 | 
08 Mar 2022
Model description paper |  | 08 Mar 2022

Building a machine learning surrogate model for wildfire activities within a global Earth system model

Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson

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Short summary
Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
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