| 研究開始時の研究の概要 |
In this study, the synoptic-scale variations of the regional Hadley cell will be first depicted and analyzed over the tropical area by utilizing observation and reanalysis data, especially from a meridional perspective. Then its modulation effect on the initialization and intensification of the tropical cyclones will be explored. During the conduction of this project, a dataset of the deep convective cloud will be generated with machine learning method. The developed algorithm can be expected to pioneer the satellite-based nighttime retrieval of deep cloud.
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| 研究実績の概要 |
In this year, we applied the cloud properties, that retrieved by our newly developed deep neural network model, to a case study of convections over the south China coastal area (SCCA). The cloud properties are analysed for SCCA offshore and inland regions respectively and different diurnal features are found for these two regions. The obtained results also suggest the inner-structures and type of convection may differ over the offshore and inland regions of SCCA due to the orthography and the background meteorological fields of this coastal area. A convection tracking algorithm is utilized to obtain parameters such as size, location, and duration time of convections. In this study, we provide a new workflow for convection / cloud system investigation by combining new techniques, and the findings can be helpful to future studies, especially these on model validation.
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