Application of WRF-LETKF System over Southern South America: Sensitivity to model physics

DILLON, MARIA EUGENIA; GARCIA SKABAR, YANINA; RUIZ, JUAN; KALNAY, EUGENIA; COLLINI, ESTELA; ECHEVARRIA, PABLO; SAUCEDO, MARCOS; MIYOSHI, TAKEMASA

Montreal

Conferencia; World Weather Open Science Conference; 2014

In order to improve the initial conditions for short?range numerical weather prediction, the Local Ensemble Transform Kalman Filter system with the Weather Research and Forecasting model (WRF-LETKF), developed at the University of Maryland, has been implemented experimentally at the National Weather Service of Argentina.In this study, results obtained from a 60-day regional data assimilation cycle over Southern South America using the WRF-LETKF system are presented. In order to consider the effect of model error, we implemented a multi-model scheme using different combinations of the cumulus and boundary layer parameterizations. Adaptive multiplicative inflation is also used to take into account observation densities and the model error. The prepbufr observation data from the National Centers for Environmental Prediction (NCEP) and the boundary conditions from the NCEP GFS forecasts were used. A super-observation technique is applied to the surface wind retrievals from the ASCAT to reduce the impactfrom the correlated observation errors.The impact of this data assimilation system on the forecast was found to be positive. We also compare the results of the multi-model physical parameterizations with a single model scheme. Finally we document the progress towards the implementation of a state-of-the-art,real time, data assimilation system at the National Weather Service of Argentina.