Japan Geoscience Union Meeting 2018

Presentation information

[EE] Oral

A (Atmospheric and Hydrospheric Sciences) » A-OS Ocean Sciences & Ocean Environment

[A-OS08] Seasonal-to-decadal climate variability and predictability

Sun. May 20, 2018 1:45 PM - 3:15 PM 301B (3F International Conference Hall, Makuhari Messe)

convener:Takashi Mochizuki(Japan Agency for Marine-Earth Science and Technology), V Ramaswamy(NOAA GFDL), Yushi Morioka(海洋研究開発機構), Chairperson:Mochizuki Takashi(Japan Agency for Marine-Earth Science and Technology), Morioka Yushi(Japan Agency for Marine-Earth Science and Technology)

2:30 PM - 2:45 PM

[AOS08-04] Seasonal-to-decadal Prediction with the Norwegian Climate Prediction Model

*Noel S Keenlyside1,2, Yiguo Wang2, Francois Counillon2,1, Ingo Bethke3, Panxi Dai4, Helene Langehaug2, Madlen Kimmritz2, Stephanie Gleixner1, Lea Svendsen1 (1.Geophysical Institute, University of Bergen and Bjerknes Centre, Norway, 2.Nansen Environmental and Remote Sensing Center, Norway, 3.Uni Research, Norway, 4.Peking University, China)

Keywords:Climate Prediction, Data assimilation, Tropical Pacific, Arctic Sea Ice, Atlantic Multi-decadal Variability

The Norwegian Climate prediction Model (NorCPM) is a fully coupled forecasting system that combines the Norwegian Earth system model with the Ensemble Kalman filter data assimilation method. We are testing the prediction skill of NorCPM with different ocean observation networks and for different time scales. At seasonal time scale, we find that NorCPM can achieve competitive skill in the ocean with assimilation of SST only e.g. in the ENSO region and in the region that extends from the Iceland Basin to the Barents Sea. As a downstream consequence, NorCPM shows skill in predicting Arctic sea ice extent (SIE) up to one year lead time from January and April at time when the influence of the ocean is consequent. Complementing the system with assimilation of ocean subsurface data have moderate impact on seasonal time scale, but it yields large improvements for longer time scale in the subpolar gyre and in the Nordic Seas. This relates to the improved representation of the salinity anomaly below the mixed layer, which causes a better initialisation of the density anomaly in the Labrador Sea.