Numerical Simulation of Sea Fog over the Yellow Sea: Comparison between PAFOG+UM and PAFOG+WRF Coupled Systems

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Thursday, 6 February 2014
Hall C3 (The Georgia World Congress Center )
WonHeung Kim, Yonsei University, Seoul, South Korea; and S. S. Yum and C. K. Kim

Safety in ground transportation and aviation traffic is highly dependent on reliable fog forecast. Some kinds of statistical method have been used in the early days of fog forecast but with the development of dependable numerical models during the past several decades, numerical prediction of fog is becoming more common. Fog is a phenomenon that occurs in the planetary boundary layer, which means that a fine resolution in vertical grids is essential for a successful numerical simulation of fog. However, implementing a fine resolution in a 3D model setting is computational very expensive. Recently, there have been several attempts to build a coupled system of a fine resolution 1D model and a 3D mesoscale model with usual grid resolution. Kim and Yum (2012 and 2013), for instance, designed the coupled system of PArameterized FOG (PAFOG) as 1D turbulence model and Weather Research and Forecasting (WRF) as 3D mesoscale model. In these studies, hourly output from WRF model was provided as the initial conditions and as horizontal advection of heat and moisture to PAFOG to account for the simulation of sea fogs over the Yellow Sea.

The Unified Model (UM) was utilized recently as the operational weather prediction model by Korea Meteorological Administration. Therefore fog forecasting needs to be done within this framework in Korea. In this study we examine the performance of the PAFOG+UM coupled system to check the reliability of the system as an operational fog forecasting system for sea fogs, which hampers aviation traffic at the Incheon International Airport, the major airport in Korea, located in a coastal island. These results are also compared with the results from the PAFOG+WRF coupled system. As Kim and Yum (2012, 2013) did, sea fogs are classified into two classes, warm and cold sea fogs, based on the difference of sea surface temperature (SST) and air temperature (T): warm sea fog if SST > T. Detailed discussion will be made in the conference.