Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: a twin experiment

Abstract

Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method for performing seasonal-to-decadal prediction and secondly, reassess the use of sea surface temperature (SST) for initialisation of these forecasts. We use the Norwegian Climate Prediction Model (NorCPM), which is based on the Norwegian Earth System Model (NorESM) and uses the deterministic ensemble Kalman filter to assimilate observations. NorESM is a fully coupled system based on the Community Earth System Model version 1, which includes an ocean, an atmosphere, a sea ice and a land model. A numerically efficient coarse resolution version of NorESM is used. We employ a twin experiment methodology to provide an upper estimate of predictability in our model framework (i.e. without considering model bias) of NorCPM that assimilates synthetic monthly SST data (EnKF-SST). The accuracy of EnKF-SST is compared to an unconstrained ensemble run (FREE) and ensemble predictions made with near perfect (i.e. microscopic SST perturbation) initial conditions (PERFECT). We perform 10 cycles, each consisting of a 10-yr assimilation phase, followed by a 10-yr prediction. The results indicate that EnKF-SST improves sea level, ice concentration, 2 m atmospheric temperature, precipitation and 3-D hydrography compared to FREE. Improvements for the hydrography are largest near the surface and are retained for longer periods at depth. Benefits in salinity are retained for longer periods compared to temperature. Near-surface improvements are largest in the tropics, while improvements at intermediate depths are found in regions of large-scale currents, regions of deep convection, and at the Mediterranean Sea outflow. However, the benefits are often small compared to PERFECT, in particular, at depth suggesting that more observations should be assimilated in addition to SST. The EnKF-SST system is also tested for standard ocean circulation indices and demonstrates decadal predictability for Atlantic overturning and sub-polar gyre circulations, and heat content in the Nordic Seas. The system beats persistence forecast and shows skill for heat content in the Nordic Seas that is close to PERFECT.

• seasonal-to-decadal prediction
• EnKF
• NorESM
• NorCPM
• SST initialisation

8. Acknowledgments

This study was partly funded by the Centre for climate dynamics at the Bjerknes Centre and the Norwegian Research Council under the NORKLIMA research project (EPOCASA; 229774/E10). This work has also received a grant for computer time from the Norwegian Program for supercomputing (NOTUR2, project number nn2993k). We would like to thank B. Backeberg and P. Raanes for their valuable comments.

Notes

¹Note that the statistic for T2M and precipitation are computed from only nine cycles because data from one of the cycle were lost.

²However, we did not test this system due to technical reasons, see Section 3.

³Observation error in EnKF-SST is 0.1°C whereas in PERFECT it is 1×10⁻⁶°C.

⁴PERSISTENCE is the yearly average prior to the start of the prediction. A 10-yr average was also attempted but reached poorer skill.