FLUXCOM-X monthly diurnal cycle of evapotranspiration on global 0.25 degree grid for 2017

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 基于FLUXCOM-X框架，该框架通过在原位涡度协方差数据上训练机器学习模型，并利用其生成全球产品。X-BASE实验作为FLUXCOM-X框架的基本配置，旨在作为基准，并包括核心气象数据、植被功能类型分类以及基于MODIS的植被指数和地表温度作为预测因子。实验中采用了XGBoost作为机器学习算法。涡度协方差数据的GPP估算基于夜间分配方法。