Articles | Volume 19, issue 3
https://doi.org/10.5194/amt-19-1059-2026
https://doi.org/10.5194/amt-19-1059-2026
Research article
 | 
16 Feb 2026
Research article |  | 16 Feb 2026

Improved estimation of diurnal variations in near-global PBLH through a hybrid WCT and transfer learning approach

Yarong Li, Zeyang Liu, and Jianjun He

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Short summary
An attention-augmented ResNet and a transfer training are implemented to derive diurnal variations in near-global planetary boundary layer height. The transfer-trained model shows superior performances compared to conventional algorithms and non-transfer trained mode. The model predicted more reliable diurnal behaviors, with daily amplitude and peak timing approaching radiosonde results.
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