FLUXCOM-X monthly transpiration on global 0.05 degree grid for 2020

X-BASE ET_T 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_T 数据集源于 FLUXCOM-X 框架，该框架通过对原位涡度相关数据集进行机器学习模型训练，并利用训练得到的模型生成全球产品。X-BASE 实验作为一种基础配置，旨在为 FLUXCOM-X 框架提供一个基准，其中包含核心气象数据、植被功能型分类以及基于 MODIS 的植被指数和地表温度作为预测因子。在机器学习算法方面，选用了 XGBoost。涡度协方差数据估算的净初级生产力（GPP）是基于夜间分合法（Nighttime Partitioning method）得出的。