Search

ABSTRACT Accurate forecasts of fog and visibility are important for many applications; while prolonged fog can adversely affect many crops, even a short duration of dense fog can lead to disruption of air and highway traffic. The genesis and dynamics of fog are a result of many processes; accurate forecasting of fog thus continues to be a challenge. A forecast model of the occurrence of fog, measured in terms of visibility, is presented. The model is formulated as an analogue model; thus the merit of the model is primarily based on its validation against observation. Two forecasts using two sets of meteorological fields are considered: one as the benchmark forecasts with visibility calculated from observed meteorological fields and the other based on meteorological forecasts from an atmospheric mesoscale model ( Weather Research and Forecasting). While the benchmark (perfect) forecasts from observed meteorological fields provide the potential skill of the model, the mesoscale forecasts provide an assessment of realizable skill in an operational setting. The validation was carried out against hourly visibility data recorded at Indira Gandhi International Airport over Delhi during the winter months ( December and January) for the period 2009-2012. Error statistics show that the analogue fog model can capture a significant part of the observed variability of fog. The forecasts have more success in forecasting intense (visibility < 500 m) and persistent (duration > 4 h) fog events. The model provides a useful forecasting tool, as shown by measures such as average error, number of false warnings and the number of misses. [ABSTRACT FROM AUTHOR]

Major challenges in modelling and forecasting fog are determining the accuracies needed in simulation of meteorological fields that determine the dynamics of fog. In particular, the meso-scale forecasts need to be tested for their ability to distinguish between foggy and non-foggy days for the important variables like wind, humidity and temperature. We evaluate forecasts from a meso-scale atmospheric model over Delhi (28°35′N; 77°12′E), a fog fog-prone metropolis, during the months December and January through 2009-2012. A comparison of composites of hourly forecasts of the meteorological fields of area-averaged 1° × 1° (28°35′N; 77°12′E) surface wind, low-level humidity and air temperatures for the observed foggy and non-foggy days shows that the forecasts do show lower winds, higher humidity and lower temperature in general for foggy days consistent with the known physical conditions for formation of fog over the region. Comparison of differences in simulated meteorological variables for days with no fog, mild fog and dense fog (characterized in terms of hourly visibility) with the corresponding values from observation show consistent and appreciable distinctions in the meteorological variables The contrasts are also found to persist at 850 mb pressure level in both observed and the simulated profiles; once again the observed vertical profiles have distinct characteristics for December and January that are simulated well by the model. Identification of these contrasts can help to calibrate model configuration and to quantify accuracy required in the meteorological forecasts for driving fog prediction models. [ABSTRACT FROM AUTHOR]