Influence of Climatology definition on the Prediction skill of CMIP6 Decadal hindcast experiments.
Abstract
Decadal climate variability (DCV) influences regional climate across the globe at multi-year to decadal time-scales. The advance prediction of phase and amplitude of various DCV modess can help us predict the state of a teleconnected regional climate. The Decadal Climate Prediction Project (DCPP) (Boer et al., 2016) endeavours to improve the skill of such predictions using predictability studies and hindcasts in the Coupled Model Intercomparison Project Phase 6 (CMIP6: Eyring et al., 2016). Hindcast experiments performed under component A of DCPP (DCPP-A) are initialised with the first forecast year 1961 and then on are initialised every year simulating 10 years. Although such experiments are initialised, the simulations drift towards the model's preferred climatological state. This drift from the observed state adversely impacts the prediction skill of the model as the experiment progresses (Hazeleger et al., 2013). Hence, climatology of such model outputs is lead time (from the initialisation) dependent and requires a definition of climatology that is lead time dependent. In this study we examine a number of definitions of lead time dependent climatology and also examine its impact on the prediction skill of model hindcasts. For this study we have chosen 9 CMIP6 models participating in DCPP having a total of 128 ensemble members.
References Boer, G. J., Smith, D. M. ., Cassou, C., Doblas-Reyes, F., Danabasoglu, G., Kirtman, B., Kushnir, Y., Kimoto, M., Meehl, G. A., Msadek, R., Mueller, W. A., Taylor, K., & Zwiers, F. (2016). The Decadal Climate Prediction Project. Copernicus GmbH. http://dx.doi.org/10.5194/gmd-2016-78 Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937-1958. https://doi.org/10.5194/gmd-9-1937-2016 Hazeleger, W., Guemas, V., Wouters, B., Corti, S., Andreu-Burillo, I., Doblas-Reyes, F. J., Wyser, K., & Caian, M. (2013). Multiyear climate predictions using two initialization strategies. Geophysical Research Letters, 40(9), 1794-1798. https://doi.org/10.1002/grl.50355- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMGC22C..05D
- Keywords:
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- Decadal Climate Variability (DCV);
- CMIP6;
- hindcast;
- DCPP;
- climatology.