Data assimilation impact using Valeri's campaign observations in Santa Catarina state

The state of Santa Catarina is often hit by extreme events such as heavy rain, windstorms, hail and eventually tornadoes. Thus, the goal of the present study was to verify how the inclusion of a larger number of observations could improve the prediction of such events. Thus, through a campaign carried out in the west of Santa Catarina, surface and radiosonde data were collected and assimilated through the GSI system. This process produced an updated initial condition to the weather prediction model WRF. The surface data assimilation had 84 new pressure observations. The radiosonde experiment had 162 observations of temperature, wind, and humidity assimilated. It was observed that the improvement of the initial condition through the insertion of the local surface and upper air data obtained during the campaign significantly improved the forecast in the conduced experiments.