Impact of in-consistency between the climate model and its initial conditions on climate prediction
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We investigated the influence of dynamical in-consistency of initial conditions on the predictive skill of decadal climate predictions. The investigation builds on the fully coupled global model “Coupled GCM for Earth Simulator” (CFES). In two separate experiments, the ocean component of the coupled model is full-field initialized with two different initial fields from either the same coupled model CFES or the GECCO2 Ocean Synthesis while the atmosphere is initialized from CFES in both cases. Differences between both experiments show that higher SST forecast skill is obtained when initializing with coupled data assimilation initial conditions (CIH) instead of those from GECCO2 (GIH), with the most significant difference in skill obtained over the tropical Pacific at lead year one. High predictive skill of SST over the tropical Pacific seen in CIH reflects the good reproduction of El Niño events at lead year one. In contrast, GIH produces additional erroneous El Niño events. The tropical Pacific skill differences between both runs can be rationalized in terms of the zonal momentum balance between the wind stress and pressure gradient force, which characterizes the upper equatorial Pacific. In GIH, the differences between the oceanic and atmospheric state at initial time leads to imbalance between the zonal wind stress and pressure gradient force over the equatorial Pacific, which leads to the additional pseudo El Niño events and explains reduced predictive skill. The balance can be reestablished if anomaly initialization strategy is applied with GECCO2 initial conditions and improved predictive skill in the tropical Pacific is observed at lead year one. However, initializing the coupled model with self-consistent initial conditions leads to the highest skill of climate prediction in the tropical Pacific by preserving the momentum balance between zonal wind stress and pressure gradient force along the equatorial Pacific.
KeywordsClimate prediction Initialization Tropical Pacific El Niño Momentum balance
The authors wish to thank Prof. Toru Nozawa for his support in compiling the radiative forcing data. The numerical calculations were carried out on the server of the Deutsches Klimarechenzentrum (DKRZ). The presented research was funded in part through a European Union 7th Framework Programme (FP7 2007–2013) project provided to the Universität Hamburg under Grant Agreement No. 308299 NACLIM (www.naclim.eu).
- Fu L-L, Cazeneve A (2000) Satellite altimetry and earth sciences: a handbook of techniques and applications. International Geophysics Series 69, Academic Press, San DiegoGoogle Scholar
- ICPO (International CLIVAR Project Office) (2011) Data and bias correction for decadal climate predictions. CLIVAR publication series no. 150. http://eprints.soton.ac.uk/171975/1/ICPO150_Bias.pdf
- Jolliffe IT, Stephenson DB (2003) Forecast verification: a practitioner’s guide in atmospheric science. Wiley, ChichesterGoogle Scholar
- Komori N, Takahashi K, Komine K, Motoi T, Zhang X, Sagawa G (2005) Description of sea-ice component of coupled ocean-sea-ice model fort he earth simulator (OIFES). J Earth Simul 4:31–45Google Scholar
- Ohfuchi W, Nakamura H, Yoshioka MK, Enomoto T, Takaya K, Peng X, Yamane S, Nishimura T, Kurihara Y, Ninomiya K (2004) 10-km mesh meso-scale resolving simulations of the global atmosphere on the Earth Simulator: preliminary outcomes of AFES (AGCM for the Earth Simulator). J Earth Simul 1:8–34Google Scholar
- Sugiura N, Awaji T, Masuda S, Mochizuki T, Toyoda T, Miyama T, Igarashi H, Ishikawa Y (2008) Development of a four-dimensional variational coupled data assimilation system for enhanced analysis and prediction of seasonal to interannual climate variations. J Geophys Res 113:C10017. doi: 10.1029/2008JC004741 CrossRefGoogle Scholar