Sensitivity of different configurations of an ensemble based data assimilation system implemented over Southern South America

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

Florianopolis

Workshop; 7th WMO Data Assimilation symposium; 2017

WMO

One of the big challenges in numerical weather prediction is to reduce the uncertainty in the initialconditions. At the National Meteorological Service (SMN) of Argentina, many efforts have beencarried out to address this issue. In this work, the regional Local Ensemble Transform Kalman Filtercoupled with the Weather Research and Forecasting model (LETKF-WRF) system implemented atthe SMN is evaluated during a two month period (November-December 2012). The domain coversmost of Southern South America with an horizontal resolution of 40 km. A 40 member ensemble isused to assimilate conventional and satellite observations (Dillon et al., 2016). A verification of 6, 24and 48-hour ensemble forecasts initialized from the LETKF-WRF system is carried out for theexperiments described below.Two different ensemble generation strategies are evaluated in this work: a single model ensemble anda multi physics ensemble that includes different choices for the cumulus and planetary boundarylayer parameterizations. This experiment shows that, overall, the multi physics approach producebetter results. The inclusion of boundary perturbations has also been explored although, it does notproduce a significant impact in the current experimental settings. Finally we explore the sensitivity tothe 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 thescarcity of radiosondes observations in Southern South