Evaluation of high-resolution WRF simulation in urban areas — Effect of different physics schemes on simulation performance in the Rhine-Main-Neckar area

Quantifying and minimizing atmospheric transport errors is key to improve meteorological modeling and to better estimate urban greenhouse gas (GHG) and air pollution emissions from measurements. The Weather Research and Forecasting Model (WRF) model has been used to simulate urban atmospheric transport in many cities globally and there exist various possible configurations especially concerning choice of physics schemes, which influence the quality of the atmospheric simulation. Here, we conduct a comprehensive evaluation of WRF on 1 km resolution for a polycentric European metropolitan area, namely the Rhine-Main-Neckar area by varying Land Surface Model (LSM), Surface Layer Model (SLM), Planetary Boundary Layer (PBL) and urban parametrization scheme configurations. We compare four month-long simulations to 2 m temperature, 10 m wind velocity and wind direction measured at 19 stations operated by the German Weather Service and to PBL height derived from radiosonde data at two locations. By showing kernel density functions in a Taylor diagram, we show the average performance of the schemes as well as the spread across different stations. We find that while the 2 m temperature and PBL height performance are most sensitive to choice of urban parametrization scheme, 10 m wind velocity and direction are most sensitive to choice of PBL scheme. Good overall performance was achieved using the Single-Layer Urban Canopy Model (SLUCM), Mellor-Yamada-Janjic (MYJ), Noah-Multiparametrization Land Surface Model (Noah-MP) and Monin-Obukhov (Janjic) (MO) schemes. While the ensemble spread is larger in winter than in summer, the choice of optimal scheme does not depend strongly on the season. • We analyze the effect of WRF physics schemes on 1 km resolution for four months. • We find that the choice of urban and PBL scheme influences model performance most. • Model performance is dominated by station characteristics. • The best overall configuration uses the SLUCM, MYJ, Noah-MP and MO schemes.