# Development of Fog Detection Algorithm Using GK2A/AMI and Ground Data
## 2 Materials and Methods  
### Materials  
In this study, mainly GK2A/AMI and numerical weather model (NWP) data, obtained from the National Meteorological Satellite Center (NMSC) of Korea Meteorological Administration (KMA), were used for fog detection. As auxiliary data, land sea mask, land cover data, and snow cover were used. Visibility data (unit: km) measured by a visibility meter obtained from KMA were used to validate the fog detection results. The characteristics of the selected channels among the 16 channels of GK2A/AMI are presented in Table 1.  
The brightness temperature at 11 \(\upmu\)m (CSR_BT11) obtained from clear sky radiance (CSR) was used as the surface temperature for clear sky to distinguish between fog and low clouds. The CSR data were obtained through the simulation of the radiative transfer model, RTTOV version 12.1, using the vertical profile data of temperature and moisture provided by the numerical weather prediction model operated by KMA [20]. The spatial resolution and temporal frequency of CSR_BT11 were 10 km and 1 h, respectively. As the spatio-temporal resolution differs between CSR_BT11 and satellite data, spatio-temporal matching was necessary for the simultaneous use of both data. Therefore, CSR_BT11 was interpolated to fit the spatio-temporal resolution of the satellite data. The land sea mask data was categorized into three types: land, sea, and coast. The coastal area was defined by \(3\times 3\) pixels from the coastline, as shown in Figure 1 (white lines). In addition, a land cover map was used to reduce the false-detected pixels in the desert area having spectral emissivity similar to that of the fog, with a lower emissivity of channel 7 than that of channel 13. The snow cover data obtained from NMSC were also used to minimize the false detection of fog in the snow-covered area. The spatial distribution of the visibility meter is shown in Figure 1. The number of stations was approximately 280, with the observing frequencies as 1 min. We used the recalculated 10 min average visibility data obtained from KMA, as the temporal frequency of the satellite fog product was 10 min. For qualitative analysis, the fog detection results of COMS Meteorological Data Processing System (CMDPS) and fog product of red-green-blue (RGB) composite using GK2A were used. The NMSC has been operationally detecting fog using CMDPS since April 2011. Here, CMDPS is a set of algorithms that retrieve various weather elements, such as fog and sea surface temperature, from COMS data, the first geostationary satellite of Korea. The fog product of RGB using GK2A uses BT12.3 \(-\) BT10.5, BT10.5 \(-\) BT3.9, and BT10.5 in red, green, and blue, respectively, like the Night Microphysics RGB used in EUMATSAT to derive a composite image [28]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Channel**} & \multirow{2}{*}{**AMI Band**} & \multicolumn{3}{c}{**Wavelength**} & \multirow{2}{*}{**Spatial Resolution [km]**} \\ \cline{3-3} \cline{5-5}  & & **(min) [\(\upmu\)m]** & **(max) [\(\upmu\)m]** \\ \hline
3 & VIS0.6 & 0.63 & 0.66 & 0.5 \\
6 & NIR1.6 & 1.60 & 1.62 & 2 \\
7 & IR3.8 & 3.74 & 3.96 & 2 \\
11 & IR8.7 & 8.44 & 8.76 & 2 \\
13 & IR10.5 & 10.25 & 10.61 & 2 \\
14 & IR11.2 & 11.08 & 11.32 & 2 \\
15 & IR12.3 & 12.15 & 12.45 & 2 \\
16 & IR13.3 & 13.21 & 13.39 & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Characteristics of the selected channels among the 16 channels of advanced meteorological imager (AMI) of GK2A used in this study. We selected 23 fog cases (23 cases \(\times\) 24 h/cases \(\times\) 6 scenes/h = 3312 scenes) that occurred around the Korean Peninsula, and 12 of these were used as training cases (T#) for determining the threshold values and 11 were used for validating the fog detection algorithm, as shown in Table 2. The total number of scenes for the training and validation cases (V#) were 1728 (=12 training cases \(\times\) 24 h \(\times\) 6 scenes/h) and 1584 (=11 validation cases \(\times\) 24 h \(\times\) 6 scenes/h), respectively.