A Diagnostic Method for Fog Forecasting Using Numerical Weather Prediction (NWP) Model Outputs

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DOI: https://doi.org/10.30564/jasr.v5i4.5068

Abstract:
An attempt has been made in the present study to forecast fog with a diagnostic method using the outputs of global NWP model. The diagnostic method is based on the combination of thresholds of meteorological variables involved in fog formation. The thresholds are computed using the observations during fog. These thresholds are applied to the output of a global NWP model for forecasting fog. The occurrence of fog is a common phenomenon during winter season over the northern plains of India. The diagnostic method is used to predict fog occurrences over three stations in north India. The proposed method is able to predict both occurrences and non-occurrences of fog at all the three stations. It is found that 94% of the fog events forecasted by the model using the diagnostic method have been actually observed at the selected stations. The performance of method in predicting fog is found best over Delhi with the highest accuracy (0.61) and probability of detection (0.60). The study signifies that diagnostic approach based on the output of a global model is a useful tool for predicting fog over a single location.
References:

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