School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Yu Zhang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Kang-En Huang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Boyang Zheng
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Based on a deep-learning method, we established a global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology. This aims to promote a comprehensive understanding of cloud dynamics and cloud–climate feedback. Closed mesoscale cellular convection (MCC) clouds occur more frequently at night, while suppressed cumulus clouds exhibit remarkable decreases. Solid stratus and MCC cloud types show clear seasonal variations.
Based on a deep-learning method, we established a global classification dataset of daytime and...