A field project that includes surface observations, remote sensing, and forecast models provides a better understanding of fog-induced low visibility and improves the parameterization of fog microphysics.

Over the years, researchers have developed parametric wind models to depict the surface winds within a tropical cyclone (TC). Most models were developed using data from aircraft flights into low-latitude (south of 30°N) TCs in the Atlantic Ocean, Gulf of Mexico, and Caribbean Sea. Such models may not adequately reproduce the midlatitude TC wind field where synoptic interaction and acceleration are more pronounced. To tailor these models for midlatitude application, latitude-dependent angular size and shape details were added by using new techniques to set values for model input parameters and by incorporating additional field-shaping procedures. A method to assess the different techniques and field-shaping procedures was developed in which qualitative and quantitative assessment was performed using five parametric models and samples of buoy and 2D surface wind data. Contingency tables and statistical scores such as mean absolute error and bias were used to select the techniques and procedures that create the most realistic depiction of low- and midlatitude TC surface wind fields.

A three-level nested rendering of a high-resolution limited-area model version of the Global Environment Multiscale configuration (GEM-LAM), running quasi-operationally at the Canadian Meteorological Centre, is evaluated for its capabilities in marine fog prediction. The model shows a general underestimation of the cloud water content at lower levels that is utilized as one of the proxies for fog and/or low stratus. A warm and dry tendency also appears at the lowest layer (a few hundreds of meters above the surface) of the vertical profiles and at screen level. The condensation scheme directly generates/dissipates the cloud water content (or fog) while boundary layer processes [such as moist turbulent kinetic energy (MoisTKE)] vertically redistribute it. However, the results presented here emphasize the significance of the accurate initial and vertical velocity fields, as well as the interactions between the condensation scheme and the radiation scheme that interacts fully with clouds. These conclusions suggest that a delicate balance among the different physical processes and dynamics is needed for a successful fog forecast.

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Three cases of widespread sea fog in Lunenburg Bay, Nova Scotia were used to evaluate the suitability of operational regional GEM forecast fields for inferring advection fog occurrences. Verification scores suggest that the objective analyses contain significant departures from observations that will affect model accuracy, given the sensitivity of fog condensation microphysics. Dew point depression (ES) scores show larger differences compared to temperature, with both influenced by surface characteristics. For objective analyses and GEM forecasts ES < 2 C seems to match fog satellite images better than the physical threshold ES £ 0 C. In addition the GEM forecasts show a general tendency towards drier conditions near the surface, therefore reconfiguring GEM to better represent condensation in the boundary layer is proposed.