Towards improving weather forecasts for Beirut using the coupled WRF-UCM.

Abstract

The coupling between the urban climate and pollution in cities has been studied extensively in the literature. In an effort to build a future pollution forecasting tool for Beirut city, obtaining meteorological variables that are representative of the city is a fundamental part. The objective of this work was to couple a single – layer urban canopy model (UCM) with the Weather Research and Forecasting model (WRF) and to fine – tune urban parameters that are relevant to Beirut city to get weather forecasts, represented by temperature, that would represent actual weather conditions in the city. Urban parameters that were tuned included the roof albedo, wall albedo, roof thermal conductivity, wall thermal conductivity, in addition to the anthropogenic heat. To get optimum values for these parameters, simulations with different values for each parameter were performed during the four seasons and compared with observations from stations that are distributed across the city. To evaluate results and determine optimum values, different statistical parameters were used such as the mean, standard deviation, mean bias, root mean square error, and correlation coefficient. The second part involved downscaling the velocity field obtained from WRF from the scale of 1 kilometer (WRF scale) to the scale of 1 meter while using mass conservation as a constraint and accounting for buildings and topography as no-flow-through boundaries.