Sensitivity of different configurations of an Ensemble based Data Assimilation System implemented over Southern South America

DILLON, MARIA EUGENIA; GARCIA SKABAR, YANINA; KALNAY, EUGENIA; RUIZ, JUAN; COLLINI, ESTELA

Florianopolis

Simposio; Seventh International WMO Symposium on Data Assimilation; 2017

One of the big challenges in numerical weather prediction is to reduce the uncertainty in the initial conditions. At the National Meteorological Service (SMN) of Argentina, many efforts have been carried out to address this issue. In this work, the regional Local Ensemble Transform Kalman Filter coupled with the Weather Research and Forecasting model (LETKF-WRF) system implemented at the SMN is evaluated during a two month period (November-December 2012). The domain covers most of Southern South America with an horizontal resolution of 40 km. A 40 member ensemble is used to assimilate conventional and satellite observations (Dillon et al., 2016). A verification of 6, 24 and 48-hour ensemble forecasts initialized from the LETKF-WRF system is carried out for the experiments described below.Two different ensemble generation strategies are evaluated in this work: a single model ensemble and a multi physics ensemble that includes different choices for the cumulus and planetary boundary layer parameterizations. This experiment shows that, overall, the multi physics approach produce better results. The inclusion of boundary perturbations has also been explored although, it does not produce a significant impact in the current experimental settings. Finally we explore the sensitivity to the assimilation of the Atmospheric Infrared Sounder (AIRS) temperature and moisture retrievals. The results indicate that the inclusion of these retrievals is a valuable alternative to deal with the scarcity of radiosondes observations in Southern South America.