## 3 Results
### Quantitative Evaluation of Fog Detection
#### 3.1.2 Fog Detection Performance by Algorithm  
The fog detection results of the GK2A_FDA validated by the nearest pixel approach, based on geographic location and time, are summarized in Table 6. The detection performance of GK2A_FDA varied substantially depending on geographic location and time of day across all evaluation metrics. Inland regions showed a lower POD of 0.57 compared to 0.67 for coastal regions; Nonetheless, the bias was also relatively lower at 4.00 versus 5.26, indicating a more stable detection performance with reduced overestimation. The POD across different time zones ranged from 0.51 to 0.83, showing moderate to good performance in daytime > nighttime > twilight. In contrast, the FAR ranged from 0.77 to 0.93 and the bias from 2.21 to 11.93, demonstrating a general tendency toward over-detection, with significant variability in bias depending on region and time. Both inland and coastal areas maintained relatively stable detection performance during nighttime, exhibiting similar bias values. In daytime conditions, by contrast, the bias increased markedly--reaching 11.93 in coastal areas and 6.12 in inland areas--indicating a strong over-detection tendency, particularly along the coast. This over-detection is associated with a structural characteristic of the GK2A_FDA as applied to coastal regions, where using both inland and ocean fog detection algorithms tends to result in higher FAR and bias during daytime. The daytime period corresponds to the dissipation stage of the fog lifecycle, during which fog dissipates from the surface [36; 37; 38] and may appear as low-level stratus clouds at ground level [39]. Nonetheless, satellites are likely to detect such conditions as fog, increasing the likelihood of false alarms [19; 31]. In inland areas during the daytime, the GK2A_FDA tends to misclassify low-level clouds as fog due to errors in the numerically modeled clear-sky surface radiance used for \(\Delta\)FTs calculation [31]. In ocean regions, the less stringent \(\Delta\)FTs threshold, introduced to enhance the detection of rapidly developing sea fog over the Bohai Sea, increases the risk of misclassifying low stratus or dissipating fog as fog [20; 40]. Fog detection in coastal areas is based on the combined results of both inland and ocean algorithms (Figure 2). If either algorithm detects fog, and five or more of the adjacent 3 \(\times\) 3 pixels are identified as fog, the target pixel is also classified as fog. This process aims to improve the fog detection levels and enhance the spatial continuity of coastal areas, which not only have the characteristics of inland and oceanic background environments but also possess unique fog occurrence characteristics. The considerable bias value during the day in coastal areas can be attributed to a combination of the following factors: (1) a relatively small number of validation points and a low frequency of fog occurrence, (2) the conservative fusion of detection results from applying both inland and ocean fog detection algorithms simultaneously to enhance spatial continuity, and (3) the misdetection of fog that dissipated after sunrise, as seen inland (Figure 2). \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Period**} & \multicolumn{3}{c}{**Inland**} & \multicolumn{3}{c}{**Coastal**} & \multicolumn{3}{c}{**Overall**} \\ \cline{2-10}  & **POD** & **FAR** & **Bias** & **POD** & **FAR** & **Bias** & **POD** & **FAR** & **Bias** \\ \hline Day & 0.69 & 0.89 & 6.12 & 0.83 & 0.93 & 11.93 & 0.72 & 0.90 & 7.34 \\ Night & 0.55 & 0.86 & 3.86 & 0.64 & 0.84 & 3.99 & 0.57 & 0.85 & 3.89 \\ Twilight & 0.51 & 0.77 & 2.21 & 0.57 & 0.83 & 3.33 & 0.52 & 0.78 & 2.36 \\ All day & 0.57 & 0.86 & 4.00 & 0.67 & 0.87 & 5.26 & 0.59 & 0.86 & 4.25 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Summary of GK2A fog detection performance by region and time. Overall represents the combined statistics for inland and coastal regions. The over-detection tendency is consistent with the study of [PERSON] et al.