An Explainable Deep Learning Model for Daily Sea Ice Concentration Forecast

As Arctic sea ice rapidly declines, accurate daily sea ice concentration (SIC) forecasts become crucial for Arctic research and operations. Emerging deep learning (DL) forecast models have the advantage of consuming fewer computational resources compared with numerical forecast systems. However, DL...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-17
Hauptverfasser:	Li, Yang, Qiu, Yubao, Jia, Guoqiang, Yu, Shuwen, Zhang, Yixiao, Huang, Lin, Lepparanta, Matti
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Arctic Correlation Daily Deep learning deep learning (DL) Environmental factors explainability marginal ice zone (MIZ) Mathematical models Modules Precipitation Predictive models Sea ice sea ice concentration (SIC) forecast Solar radiation Wind forecasting
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