| description abstract | his paper describes a three-dimensional immersed boundary method (IBM) that facilitates the explicit resolution of complex terrain within the Weather Research and Forecasting (WRF) model. Two interpolation methods?trilinear and inverse distance weighting (IDW)?are used at the core of the IBM algorithm. This work expands on the previous two-dimensional IBM algorithm of Lundquist et al., which uses bilinear interpolation. Simulations of flow over a three-dimensional hill are performed with WRF?s native terrain-following coordinate and with both IB methods. Comparisons of flow fields from the three simulations show excellent agreement, indicating that both IB methods produce accurate results. IDW proves more adept at handling highly complex urban terrain, where the trilinear interpolation algorithm fails. This capability is demonstrated by using the IDW core to model flow in Oklahoma City, Oklahoma, from intensive observation period 3 (IOP3) of the Joint Urban 2003 field campaign. Flow in Oklahoma City is simulated concurrently with an outer domain with flat terrain using one-way nesting to generate a turbulent flow field. Results from the IBM-WRF simulation of IOP3 compare well with observations from the field campaign, as well as with results from an urban computational fluid dynamics code, Finite Element Model in 3-Dimensions and Massively Parallelized (FEM3MP), which used body-fitted coordinates. Using the FAC2 performance metric from Chang and Hanna, which is the fraction of predictions within a factor of 2 of observations, IBM-WRF achieves 100% and 71% for velocity predictions using cup and sonic anemometer observations, respectively. For the passive scalar, 53% of the model predictions meet the FAC5 (factor of 5) criteria. | |
