AROME-WMED, a real-time mesoscale model designed for the HyMeX special observation periods

• Main Authors: N. Fourrié, É. Bresson, M. Nuret, C. Jany, P. Brousseau, A. Doerenbecher, M. Kreitz, O. Nuissier, E. Sevault, H. Bénichou, M. Amodei, F. Pouponneau
• Format: Article
• Language: English
• Published: Copernicus Publications 2015-07-01
• Series: Geoscientific Model Development
• Online Access: http://www.geosci-model-dev.net/8/1919/2015/gmd-8-1919-2015.pdf

During autumn 2012 and winter 2013, two special observation periods (SOPs) of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) took place. For the preparatory studies and to support the instrument deployment during the field campaign, a dedicated version of the operational convective-scale Application of Research to Operations at Mesoscale (AROME)-France model was developed: the AROME-WMED (West Mediterranean Sea) model. It covers the western Mediterranean basin with a 48 h forecast range. It provided real-time analyses and forecasts which were sent daily to the HyMeX operational centre to forecast high-precipitation events and to help decision makers on the deployment of meteorological instruments. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. Some specific data of the HyMeX SOP were assimilated in real time. <br><br> The forecast skill of AROME-WMED is then assessed with objective scores and compared to the operational AROME-France model, for both autumn 2012 (05 September to 06 November 2012) and winter 2013 (01 February to 15 March 2013) SOPs. The overall performance of AROME-WMED is good for the first HyMeX special observation period (SOP1) (i.e. mean 2 m temperature root mean square error (RMSE) of 1.7 °C and mean 2 m relative humidity RMSE of 10 % for the 0–30 h forecast ranges) and similar to those of AROME-France for the 0–30 h common forecast range (maximal absolute difference of 2 m temperature RMSE of 0.2 °C and 0.21 % for the 2 m relative humidity); conversely, for the 24–48 h forecast range it is less accurate (relative loss between 10 and 12 % in 2 m temperature and relative humidity RMSE, and equitable threat score (ETS) for 24 h accumulated rainfall), but it remains useful for scheduling observation deployment. The characteristics of parameters, such as precipitation, temperature or humidity, are illustrated by one heavy precipitation case study that occurred over the south of Spain.