| 研究実績の概要 |
In the last year, we developed a cloud retrieval model with a deep neural network (DNN) algorithm. When comparing to the traditional physics-based models, the new breakthrough is that as an infrared method in nature, our new model extends the predictable cloud optical thickness to ~200 with an overall relative bias less than 20%. This new model can be realistically applied to severe weather monitoring and mesoscale convective system studies. This work has been published on Remote Sensing of Environment, which is a Top journal in the field of remote sensing. With the DNN retrieved cloud properties, we further conducted a case study on the cloud evolutions in offshore and inland mesoscale convective systems over the south China coastal area.
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