Workshop on Predictability, dynamics and applications research using the TIGGE and S2S ensembles

The intraseasonal oscillation (e.g., the MJO and the BSISO) is the major source of predictability of extreme weather in a S2S time scale (e.g., 3-4 weeks). Many authors examined the predictability of the MJO and the BSISO in subjectively selected months. Recently, Kikuchi et al. (2016) applied a method which can objectively determine which ISO mode is dominant in a given day to a cloud-system resolving climate simulation data. They pointed out that the model has the BSISO bias even in boreal winter and simulated amplitude of ISO is about half of the observation. Considering that the models drift toward their own climatology in some timescales, it is helpful for model improvement to know how the drift occurs. Here we applied Kikuchi’s method to the S2S data. All the S2S models examined show the BSISO bias even in boreal winter and some of those monotonically increase in the BSISO appearance frequency with the lead time. This result obviously indicates that the BSISO bias in boreal winter occurs from the drift of the model climatology. We will discuss what causes the drift at the presentation.