Assessment of integrated water vapor derived from AROME model using GPS data over Morocco

A good prediction of water vapor is a key element to improve the forecast quality of heavy precipitation events. The aim of this work is evaluating the integrated water vapor (IWV) from AROME model, for operational meteorological purposes, using IWV data from nine Global Positioning System (GPS) permanent sites in Morocco. This validation was carried out through a statistical assessment for the period from the 20th February 2018 to the 20th March 2018 using 3-hourly forecasts of the AROME model. The results show a good ability of AROME model in simulating IWV, with a correlation coefficient of 0.83 along with a standard deviation of 4.34 mm and a bias about 0.41 mm. In addition, the analysis of an extreme precipitation event in the north part of Morocco was carried out. During this case study an increase in IWV from AROME was observed few hours before the occurrence of precipitation event followed by a sharp decrease. This study demonstrates the good potential of AROME model in predicting IWV especially during rainfall situation, which could be an efficient tool for operational forecasting.