WRF high resolution simulation of an extreme rainfall event over Douala (Cameroon): a case study

An unusual extreme precipitation affected the Douala town of Cameroon during 19–20 June 2015. 24-h accumulated rainfall recorded, exceeded 80 mm/day and led to flash floods, loss of life and severe damage in the area. This study presents the results of a numerical simulation of this event using the Weather Research and Forecasting (WRF) model over three domains with horizontal resolutions of 27, 9 and 3 km. Soundings from Douala International Airport show that this event was associated with the downpours, thunderstorms and high values of Vertical Integral of Water Vapour indicating the intense stormy episode. The values of the Convective Available Potential Energy obtained from the soundings clearly indicate that there was a persistent instability in Douala during this period. In addition the satellite images from infrared channel show that there was the clouds with strong vertical development showing the presence of a stormy area extending on the coasts of Cameroon and Nigeria. Using the WRF model, initialized and bounded by the National Center for Environmental Prediction Global Forecasting System 3 h products, the episode was successfully simulated. The model was able to reproduce the important meteorological features associated with this event, which include good simulation of the Vertical Integral of Water Vapour with the magnitude similar to that obtained from soundings. Relative humidity and low level wind at 850 hPa were also well simulated by the model compared to the ERAI reanalyses data. The surface air was almost saturated in Douala and its surroundings. The prevailing wind was southwest (monsoon) indicating a permanent supply of moisture from the Atlantic Ocean to the continent. The simulated precipitation also compares favorably to the observation and Tropical Rainfall Measuring Mission in term of spatial and total accumulated amount. The WRF model appears to be a tool that might assist forecasters throughout rainy seasons in Central Africa to successfully predict such events. © 2017, Springer International Publishing AG.