Evaluation of an ensemble based data assimilation system over Southern South America: Sensitivity to the use of perturbed boundary conditions.

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

Santiago de Chile

Conferencia; 11th International Conference on Southern Hemisfere Meteorology and Oceanography; 2015

p { margin-bottom: 0.21cm; direction: ltr; color: rgb(0, 0, 0); }p.western { font-family: "Times New Roman",serif; font-size: 12pt; }p.cjk { font-family: "MS Mincho","ＭＳ 明朝",monospace; font-size: 12pt; }p.ctl { font-family: "Times New Roman",serif; font-size: 12pt; }a:link { color: rgb(0, 0, 255); }One of the big challenges in numerical weather prediction is toreduce the uncertainty in the initial conditions. At the NationalMeteorological Service (SMN) of Argentina, many efforts have beencarried out to address this issue: a regional data assimilationsystem is being developed using the Local Ensemble Transform KalmanFilter (LETKF) coupled with the Weather Research and ForecastingModeling System (WRF). The selection of this method is motivatedmainly because it generates an ensemble of initial conditions thatcan be used for ensemble forecasting and also by the favorableresults obtained by many authors and its computational efficiency. Inthis manner, two important objectives are achieved: the improvementof the initial conditions and the explicit estimation of itsuncertainty that can be propagated forward in time using an ensembleof forecasts.In this work, the LETKF-WRF data assimilation system is evaluatedover Southern South America during a two month period includingNovember and December 2012. A horizontal resolution of 40 km and 40ensemble members are used, and the analyses are obtained with a 3hour frequency, assimilating the observations available in thePREPBUFR files from the Global DataAssimilation System.Encouraging results about the performance of this regional dataassimilation system have been achieved with different configurationsby the authors, for example with a multischeme structure or with theinclusion of the vertical profiles retrieved from the AtmosphericInfrared Sounder (AIRS) in the assimilation cycles. In this work weexplore the sensitivity of the analysis accuracy to the use ofperturbed boundary conditions. Previous studies demonstrated thatthis can be done in order to explicitly represent the uncertainty inthe boundary conditions in the data assimilation system, thusimproving its performance. We compare the results of the analysis cycles obtained without usingperturbations at the boundaries with an experiment where the boundaryconditions are perturbed using random balanced perturbations. Theseperturbations are generated as scaled differences of randomlyselected atmospheric states as described by the Global ForecastingSystem (GFS) forecasts. The impact of lateral boundary perturbations upon the assimilationsystem is evaluated through the verification of the 6 hour forecasts.In addition, an intense precipitation case study is selected in orderto evaluate the performance of a 48 hour forecast. The results areencouraging and indicate that boundary conditions perturbationsshould be considered for the operational implementation of thissystem. Future work would focus on the implementation of a completeconfiguration taking advantage of a multischeme ensemble, theassimilation of the AIRS retrievals and the perturbed boundaryconditions altogether.