EGU21-10380
https://doi.org/10.5194/egusphere-egu21-10380
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Relating model bias and prediction skill in the equatorial Atlantic

Francois Counillon1,2, Noel Keenlyside1,2, Thomas Toniazzo3, Shunya Koseki2, Teferi Demissie3,4, Ingo Bethke2, and Yiguo Wang1
Francois Counillon et al.
  • 1NERSC, Bergen, Norway (francois.counillon@nersc.no)
  • 2Geophysical Institute, University of Bergen, Norway
  • 3NORCE Norwegian Research Centre, Bergen, Norway
  • 4CGIAR Research Program on Climate Change, Agriculture and Food Security Addis Ababa, Ethiopia

We investigate the impact of large climatological biases in the tropical Atlantic on reanalysis and seasonal prediction performance using the Norwegian Climate Prediction Model (NorCPM) in a standard and an anomaly coupled configuration. Anomaly coupling corrects the climatological surface wind and sea surface temperature (SST) fields exchanged between oceanic and atmospheric models, and thereby significantly reduces the climatological model biases of precipitation and SST. NorCPM combines the Norwegian Earth system model (NorESM) with the Ensemble Kalman Filter and assimilates SST and hydrographic profiles. We perform a reanalysis for the period 1980-2010 and a set of seasonal predictions for the period 1985-2010 with both model configurations. Anomaly coupling improves the accuracy and the reliability of the reanalysis in the tropical Atlantic, because the corrected model enables a dynamical reconstruction that satisfies better the observations and their uncertainty.  Anomaly coupling also enhances seasonal prediction skill in the equatorial Atlantic to the level of the best models of the North American multi-model ensemble, while the standard model is among the worst. However, anomaly coupling slightly damps the amplitude of Atlantic Niño and Niña events. The skill enhancements achieved by anomaly coupling are largest for forecast started from August and February. There is strong spring predictability barrier, with little skill in predicting conditions in June. The anomaly coupled system show some skill in predicting the secondary Atlantic Niño-II SST variability that peaks in November-December from August 1st.

How to cite: Counillon, F., Keenlyside, N., Toniazzo, T., Koseki, S., Demissie, T., Bethke, I., and Wang, Y.: Relating model bias and prediction skill in the equatorial Atlantic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10380, https://doi.org/10.5194/egusphere-egu21-10380, 2021.

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