Ensemble-based Sensitivity Analysis applied to African Easterly Waves

An ensemble Kalman filter (EnKF) coupled to the Advanced Research version of the Weather Research and Forecasting (WRF) model is used to generate ensemble analyes and forecasts of a strong African Easterly Wave (AEW) during the African Monsoon Multidisciplinary Analysis field campaign. Ensemble sensitivity analysis is then used to evaluate the impact of initial condition errors on AEW amplitude and position forecasts at two different initialization times. WRF forecasts initialized at 0000 UTC 8 September 2006 prior to the amplification of the AEW are characterized by large ensemble variance as compared to forecasts initialized 48 hours later when the AEW is within a denser observation network. Short lead time amplitude forecasts are most sensitive to the mid-tropospheric meridional winds and the midtropospheric θe, while at longer lead times, mid-tropospheric θe errors have a larger impact. For AEW longitude forecasts, the largest sensitivities are associated with the θe downstream of the AEW, and to a lesser extent, the meridional winds. Ensemble predictions of initial condition errors impact the AEW amplitude and position compare qualitatively well with perturbed integrations of the WRF model. Much of the precipitation associated with the AEW is generated by the Kain-Fritsch cumulus parameterization, thus the initial-condition sensitivities are also computed for ensemble forecasts that use the Betts-Miller-Janjic and Grell cumulus parameterization scheme, and a high-resolution nested domain with explicit convection. While the 12 hour AEW amplitude forecast is characterized by consistent initial-condition sensitivity among the different schemes, there is more variability beyond 24 hours. In contrast, the AEW position forecast is sensitive to the downstream thermodynamic profile regardless of cumulus scheme.