Abstract
Abstract. A novel predictive model was built for eddy propagation trajectory
using the multiple linear regression method. This simple model relates
various oceanic parameters to eddy propagation position changes in the
northern South China Sea (NSCS). These oceanic parameters mainly represent
the effects of β and mean flow advection on the eddy propagation. The
performance of the proposed model has been examined in the NSCS based on five
years of satellite altimeter data and demonstrates its significant
forecasting skills over a 4-week forecast window compared to the traditional
persistence method. It was also found that the model forecasting accuracy is
sensitive to eddy polarity and the forecast season.
Subject
Cell Biology,Developmental Biology,Embryology,Anatomy
Reference47 articles.
1. Aberson, S. D. and Sampson, C. R.: On the predictability of tropical cyclone
tracks in the northwest pacific basin, Mon. Wea. Rev., 131, 1491–1497, 2003.
2. Ali, M. M., Kishtawal, C. M., and Jain, S.: Predicting cyclone tracks in the
north Indian Ocean: An artificial neural network approach, Geophys. Res.
Lett., 34, L04603, https://doi.org/10.1029/2006GL028353, 2007.
3. Bao, S., Zhang, R. Wang, H., Yan, H., and Yu, Y.: Salinity profile estimation
in the Pacific Ocean from satellite Surface salinity observations, J. Atmos.
Oceanic. Technol., 36, 53–68, 2019.
4. Cai, S., Long, X., Wu, R., and Wang, S.: Geographical and monthly variability
of the first baroclinic rossby radius of deformation in the south china sea,
J. Mar. Syst., 74, 711–720, 2008.
5. Canes, M. R.: Description and evaluation of GDEM-V3.0, Rep.
NRL/MR/7330-09-9165, Nav. Res. Lab, Washington, DC, 2009.
Cited by
19 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献