Advection fog locations series#

In particular, the Weather Research and Forecasting (WRF) model ( Skamarock et al., 2008), which allows the use of different combinations of physical parameterizations and technical configurations, has been used to investigate the sensitivity of model attributes in fog simulations.

Several factors that influence fog prediction, such as the initial conditions ( Rémy et al., 2012 Bari et al., 2015), model resolution ( Tardif, 2007 Tang et al., 2009 Van der Velde et al., 2010), terrain ( Golding, 1993), turbulence ( Li and Zheng, 2015), and vegetation ( von Glasow and Bott, 1999), have been investigated by using NWP models. Significant progress has been made in fog prediction and visibility parameterization with the development of several fog prediction models (e.g., Bergot and Guedalia, 1994 Clark and Hopwood, 2001a, b Bott and Trautmann, 2002), visibility algorithms ( Doran et al., 1999 Stoelinga and Warner, 1999 Bieringer et al., 2006 Gultepe et al., 2006, 2009 Bang et al., 2009 Gultepe and Milbrandt, 2010 Creighton et al., 2014), and improved numerical weather prediction (NWP) models for fog prediction and simulations (e.g., Fu et al., 2010 Kim and Yum, 2012 Román-Cascón et al., 2012, 2016 Hu et al., 2014 Payra and Mohan, 2014). Accurate prediction of advection fog at ZSPD and in its vicinity is becoming more and more important for providing better aviation service and reducing delays and economic loss. For instance, over the east coast of China, Shanghai Pudong International Airport (ZSPD) is a major aviation hub for Asia, where the air traffic is frequently disturbed by advection fog from the East China Sea (ECS) in winter and spring ( Yuan and Chen, 2013). A common type of fog that often influences coastal regions is advection fog, which forms when quite warm, moist air is blown across a cooler surface. The adverse effects of fog on human activities, especially on aviation, marine, and land transportation, are well known (e.g., Bergot et al., 2007 Fabbian et al., 2007 Gultepe et al., 2007, 2015 Fu et al., 2010 Niu et al., 2010 Stolaki et al., 2012). The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.įog is a weather phenomenon caused by the suspension of tiny liquid water droplets or ice crystals in the air at or near the earth’s surface, during which horizontal visibility is less than 1 km. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi-cal processes to spin up adequately during the fog simulation. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset.

Additional numerical experiments are performed to examine the physical processes associated with the fog event. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD.

Advection fog locations series#

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model.