Visibility Data Assimilation and Prediction Using an Observation Network in South Korea

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There have been many studies to improve visibility forecast skills using numerical models, but their performance still remains behind the forecast skills for other meteorological phenomena. This study attempted to improve visibility forecasts using a newly established automatic visibility observation network composed of 291 forward-scattering sensors in South Korea. In the analysis of recent 3-year visibility observations, clear days (visibility above 20 km) were reported for 46% of the days, and fog cases (visibility less than 1 km) accounted for 1.58% of the total observations. The Very short-range Data Assimilation and Prediction System (VDAPS) of the Korea Meteorological Administration (KMA) assimilated the visibility observations based on the Met Office Unified Model with visibility data assimilation of Clark et al. (Q J R Meteorol Soc 134:1801–1816, 2008). Prior to the data assimilation, a precipitation check eliminated visibility data with precipitation (9.4% in total, 23% for visibility less than 1 km), and a consistency check removed visibility observations that were inappropriate to relative humidity, temperature, and pressure. In a case study on two consecutive fog days, visibility forecast skills were improved by applying visibility data assimilation, mostly through modifications of aerosol concentrations. A 3-month model run in the winter of 2016 showed a positive bias in visibility predictions, especially for the low-visibility cases. Visibility data assimilation improved the prediction skills, but the positive effects were limited within 9 forecast hours and were smaller for extremely low-visibility events. Sensitivity experiments were performed using local aerosol observations with a larger number of smaller aerosol particles. Modifications in aerosol properties made better results in frequency bias for the whole forecast ranges and also improved the equitable threat score (ETS) for relatively longer forecast hours (more than 4 h).