| Abstrakt: |
Accurate depiction of meteorological conditions, especially within the planetary boundary layer (PBL), is essential for fog forecasting. This study examines the sensitivity of the performance of the Weather Research and Forecast (WRF) model to the use of four different PBL schemes [Yonsei University (YSU), asymmetric convective model version 2 (ACM2), quasinormal scale elimination (QNSE), and Mellor-Yamada-Nakanishi-Niino version 3.0 (MYNN3)]. For this case study we have taken the fog event occurred in November 23-24, 2020. Surface observed temperature and relative humidity, furthermore, sounding data are compared with the output of the 36 hours, high-resolution weather forecast. The horizontal extension of the simulated fog is compared with satellite observations. The visibility is calculated from the prognostic variables of drop number concentration and mixing ratio. The simulated visibility and fog duration are validated by the visibility and fog duration evaluated by ceilometer observations. Validation of thermodynamical values such as 2-m temperature and relative humidity reveals, that during most of the simulation time, the bias is significant between the simulated and observed data. Results show that the PBL parameterization scheme significantly impacts fog microphysics also. The QNSE scheme results in unrealistic early formation of the fog, and too large liquid water content. YSU and ACM2 simulated the duration of fog to be rather short comparing with the other two PBL schemes. The best fitting with observed data is found in the case of MYNN3 PBL schemes. [ABSTRACT FROM AUTHOR] |
