FLUXCOM-X daily evapotranspiration on global 0.25 degree grid for 2014

X-BASE ET is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.

Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
Nelson, J.A., Walther, S., Jung, M., Gans, F., Kraft, B., Weber, U., Hamdi, Z., Duveiller, G., Zhang, W., 2023. FLUXCOM-X-BASE. https://doi.org/10.18160/5NZG-JMJE

X-BASE ET 源自 FLUXCOM-X 框架，该框架通过在原位涡相关数据上训练机器学习模型，并利用这些模型生成全球产品。X-BASE 实验作为一种基本配置，旨在为 FLUXCOM-X 框架提供基准，其预测因子包括核心气象数据、植被功能型分类以及基于 MODIS 的植被指数和地表温度。实验中采用了 XGBoost 作为机器学习算法。涡相关数据中的 GPP 估算基于夜间分割方法。

已发表论文：https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
Nelson, J.A., Walther, S., Jung, M., Gans, F., Kraft, B., Weber, U., Hamdi, Z., Duveiller, G., Zhang, W., 2023. FLUXCOM-X-BASE. https://doi.org/10.18160/5NZG-JMJE