STEMMUS SCOPE emulator train test example data of 2014

The "csv" file contains land-atmosphere variables and latent heat flux (LEtot) simulated by STEMMUS-SCOPE (soil-plant model), version 1.5.0, see GitHub repository STEMMUS-SCOPE. The data spreads over 19 Fluxnet sites and for the year 2014 with hourly intervals. For more information see EcoExtreML project. This data was used as training data pairs to develop an emulator using a random forests regression algorithm, the "onnx" file. The target variable is "latent heat flux (LEtot)" and features are land-atmosphere variables. For more information about the emulator, see GitHub repository STEMMUS-SCOPE Emulator. The model and data are used to create a tutorial on applying an explainability method, for example, Kernel SHAP using the package DIANNA. For more information see Deep Insight and Neural Network Analysis (DIANNA) project.本CSV文件包含由STEMMUS-SCOPE（土壤-植物模型）v1.5.0版本模拟得到的陆气变量与总潜热通量（LEtot），相关信息可参阅GitHub仓库STEMMUS-SCOPE。该数据覆盖19个通量网（Fluxnet）站点，时间范围为2014年，采样间隔为每小时1组。如需了解更多信息，请参阅EcoExtreML项目。 该数据被用作训练数据对，以基于随机森林回归算法开发模拟器（onnx文件）。其目标变量为总潜热通量（LEtot），特征变量为陆气变量。如需了解该模拟器的更多细节，请参阅GitHub仓库STEMMUS-SCOPE Emulator。 本模型与数据被用于制作一则教程，讲解可解释性方法的应用实践——例如借助DIANNA包实现Kernel SHAP（核SHAP）。如需了解更多相关信息，请参阅深度洞察与神经网络分析（Deep Insight and Neural Network Analysis，DIANNA）项目。