Dataset: The 2023 global chlorophyll-a profiles inverted by the chlorophyll-a random forest model

This 2023 global chlorophyll-a profiles dataset was inverted using our chlorophyll-a random forest model. This is a machine learning-based method for merging satellite and Argo data to extend surface chlorophyll-a to depth. Figure 1 shows the continuous distribution map of different water layers generated by the data-interpolating variational analysis (DIVA) method for this dataset.本数据集为2023年全球叶绿素-a（chlorophyll-a）剖面数据集，通过我们的叶绿素-a随机森林模型（random forest model）反演得到。该方法基于机器学习技术，通过融合卫星遥感数据与Argo数据（Argo data），将表层叶绿素-a的观测范围延伸至深层海域。图1展示了采用数据插值变分分析（data-interpolating variational analysis, DIVA）方法针对本数据集生成的不同水层连续分布图谱。