FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites

Lai, Jie; Zhang, Yuan; Wang, Anzhi; Fei, Wenli; Diao, Yiwei; Li, Rongping; Wu, Jiabing

doi:https://doi.org/10.5194/gmd-18-5115-2025

Articles | Volume 18, issue 16

https://doi.org/10.5194/gmd-18-5115-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-5115-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 16

Model description paper

|

22 Aug 2025

Model description paper |

| 22 Aug 2025

FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites

Jie Lai, Yuan Zhang, Anzhi Wang, Wenli Fei, Yiwei Diao, Rongping Li, and Jiabing Wu

Supplement

https://doi.org/10.5194/gmd-18-5115-2025-supplement

Data sets

FLAML-main [Data set] Laijie https://doi.org/10.5281/zenodo.14874754

FLAML\_LUE data and code Laijie https://doi.org/10.5281/zenodo.15477703

Model code and software

FLAML\_LUE data and code Laijie https://doi.org/10.5281/zenodo.15477703

Short summary

In this study, a new model called FLAML-LUE was created by combining the Fast Lightweight Automated Machine Learning (FLAML) model with light use efficiency (LUE) models; the latter provides the key variables of vegetation growth for modeling. Such knowledge- and data-driven models aim to reduce the large uncertainty in estimating gross primary productivity (GPP).