EGU2020-6584
https://doi.org/10.5194/egusphere-egu2020-6584
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Season-dependent predictability and error growth dynamics for La Nina predictions

Junya Hu1, Wansuo Duan2, and Qian Zhou3
Junya Hu et al.
  • 1Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China (junya1990606@163.com)
  • 2Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China(duanws@lasg.iap.ac.cn)
  • 3National Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing, China(zhouqian09@gmail.com )

The “spring predictability barrier” (SPB) is a well-known characteristic of ENSO prediction, which has been widely studied for El Niño events. However, due to the nonlinearity of the coupled ocean–atmosphere system and the asymmetries between El Niño and La Niña, it is worthy to investigate the SPB for La Niña events and reveal their differences with El Niño. This study investigates the season-dependent predictability of sea surface temperature (SST) for La Niña events by exploring initial error growth in a perfect model scenario within the Community Earth System Model. The results show that for the prediction through the spring season, the prediction errors caused by initial errors have a season-dependent evolution and induce an SPB for La Niña events. Two types of initial errors that often yield the SPB phenomenon are identified: the first are type-1 initial errors showing positive SST errors in the central-eastern equatorial Pacific accompanied by a large positive error in the upper layers of the eastern equatorial Pacific. The second are type-2 errors presenting an SST pattern with positive errors in the southeastern equatorial Pacific and a west–east dipole pattern in the subsurface ocean. The type-1 errors exhibit an evolving mode similar to the growth phase of an El Niño-like event, while the type-2 initially experience a La Niña-like decay and then a transition to the growth phase of an El Niño-like event. Both types of initial errors cause positive prediction errors for Niño3 SST and under-predict the corresponding La Niña events. The resultant prediction errors of type-1 errors are owing to the growth of the initial errors in the upper layers of the eastern equatorial Pacific. For the type-2 errors, the prediction errors originate from the initial errors in the subsurface layers of the western equatorial Pacific. These two regions may represent the sensitive areas of targeted observation for La Niña prediction. In addition, the type-2 errors in the equatorial regions are enlarged by the recharge process from 10°N in the central Pacific during the eastward propagation. Therefore, the off-equatorial regions around 10°N in the central Pacific may represent another sensitive area of La Niña prediction. Additional observations may be prioritized in these identified sensitive areas to better predict La Niña events.

How to cite: Hu, J., Duan, W., and Zhou, Q.: Season-dependent predictability and error growth dynamics for La Nina predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6584, https://doi.org/10.5194/egusphere-egu2020-6584, 2020