Monday, 26 June 2017
Salon A-E (Marriott Portland Downtown Waterfront)
Forecast skill of convectively coupled equatorial waves (CCEWs) is assessed in two operational forecast models, the NCEP Global Forecast System (GFS) and the ECMWF Integrated Forecast System (IFS) model. Guidance from both models was used during NOAA’s 2016 El Niño Rapid Response field campaign and it was observed that both models perform with much higher skill for mid-latitude precipitation forecasts than for the tropics. Here we first examine the forecast skill of the dynamical variables during 2015 and since a large contribution to predictability in the tropics is due to CCEWs, we focus mainly on these large scale features. Both model analyses are compared and the differences are shown to be smaller than differences to global reanalyses products. After 10 days the GFS converges to a double ITCZ in the central Pacific consistent with low-level divergence at the equator and off-equatorial convergence in both hemispheres. Coherence spectra of observed precipitation and model divergence show signals along CCEW dispersion curves, indicating that CCEWs are initialized in the model analyses. In addition, we find that convectively coupled equatorial Kelvin waves coherently propagated for only about 3 days in the GFS and 7 days in the IFS. This difference in forecast skill is consistent with the differences in the low-level flow that each model converges to. The divergence along the equator that develops in the GFS is not conducive to convectively coupled equatorial Kelvin waves, whereas the IFS divergence field is. This indicates that initialization of CCEWs is not the limiting factor in forecasting this type of variability, but rather the relationship between large scale dynamics and the parametrization of moist convective processes is. This issue raises the question of the respective role of CCEWs and the basic model state as well as their interplay in deteriorating tropical forecast skill.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner