LAUSR

Abstract. This paper presents the results of several observing system experiments (OSEs) performed with AROME-WMED. This model is the HyMeX (Hydrological cycle in the Mediterranean Experiment) dedicated version (Fourrie et al., 2019) of the French operational meso-scale model AROME. The second and final reanalyses assimilated most of all available data for a 2 month period corresponding to the first Special Observation Period of HyMeX. In order to assess the impact of various observation data set assimilation on the forecasts, several OSEs or also-called denial experiments, were carried out. In this study, impact of a dense reprocessed network of high quality Global Navigation Satellite System (GNSS) Zenithal Total Delay (ZTD) observations, reprocessed wind-Profilers, lidar-derived vertical profiles of humidity (ground and airborne) and Spanish radar data, is thus discussed. Among the evaluated observations, it is found that the ground-based GNSS ZTD data set provides the largest impact on the analyses and the forecasts as it represents an evenly spread and frequent data set providing information at each analysis time over the AROME-WMED domain. The impact of the reprocessing of GNSS ZTD data also improves the forecast quality but this impact is not statistically significant. The assimilation of the Spanish radar data improves the very short term forecast quality as well as the short term forecasts but this impact remains located over Spain. Marginal impact from wind profilers was observed on wind background quality. No impacts have been found regarding lidar data as they represent a very small data set.