Unified Model Atmospheric Forecast Model Data for Machine Learning Cloud-Base Height

Unified Model data, in pp format, for machine learning of cloud-base height based on profiles of temperature, humidity, pressure and cloud fraction. The model configuration is Global Atmosphere 6, running with a resolution of N320 (which is coarser than what was running operationally at the time). Each simulation is run for 24 hours, re-initialising every 24 hours. A separate data file is provided every 6 hours. Data points are on a latitude-longitude grid in the horizontal and on a stretched grid in the vertical. See https://gmd.copernicus.org/articles/10/1487/2017/ for details of the model configuration. Data from January 2016 is for training. Data from July 2017 is for development/validation Data from October 2017 is for final testing.

本数据集为统一数值模式（Unified Model）产出数据，采用PP格式存储，用于面向云底高度的机器学习研究，其输入特征为温度、湿度、气压与云量廓线。该模式采用全球大气6版（Global Atmosphere 6）配置，运行分辨率为N320，相较于同期业务运行的模式分辨率更粗。每次模拟时长为24小时，每24小时执行一次重新初始化。每6小时生成一份独立数据文件。数据在水平维度采用经纬度网格布局，垂直维度采用拉伸网格。模式配置的详细信息可参见文献：https://gmd.copernicus.org/articles/10/1487/2017/。数据集划分规则如下：2016年1月的数据用于模型训练，2017年7月的数据用于模型开发与验证，2017年10月的数据用于最终测试。