## 4 Results
### Cloud Mask  
The AGRI 4-km cloud mask was evaluated using the collocated MODIS/Terra Collection 6 (i.e., MOD06) level-2 1-km cloud detection products. As earlier discussed (Section 3.1), either one or several MODIS cloud mask retrievals can fall within a single 4-km AGRI cloud mask retrieval. In order to mitigate the uncertainty of comparison due to sub-pixel inhomogeneity [36], only AGRI pixels where all the collocated MODIS cloud mask retrievals were identical (i.e., either all clear, all probably clear, all probably cloudy, or all cloudy) were included in the statistics. Figure 2 shows the fraction of the various identification results of the AGRI cloud mask for collocated samples when the MODIS cloud detection results were \"cloudy\", \"probably cloudy\", \"probably clear\", and \"clear\" respectively. The four colors represent these four different scenes. The evaluation results are presented as a fractional agreement. Fractional agreement is similar to POD score. The difference between POD score and fractional agreement is that the POD score is calculated from the matched sample dataset that only includes the pixels classified as \"cloudy\" or \"clear\" by both AGRI and MODIS, while the fractional agreement is calculated based on all matched samples that are flagged either \"cloudy\", \"probably cloudy\", \"probably clear\", or \"clear\". \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{**Month**} & **Collocated** & \multicolumn{4}{c}{**Cloudy**} & \multicolumn{4}{c}{**Clear**} & \multirow{2}{*}{**HR**} \\ \cline{2-2} \cline{4-9}  & **Samples** & & **Agreement** & **POD** & **FAR** & **Agreement** & **POD** & **FAR** \\ \hline Jun. & 615,076 & 0.941 & 0.971 & 0.078 & 0.726 & 0.868 & 0.051 & 0.932 \\ Jul. & 667,130 & 0.942 & 0.975 & 0.064 & 0.764 & 0.909 & 0.035 & 0.947 \\ Aug. & 714,889 & 0.915 & 0.972 & 0.137 & 0.713 & 0.832 & 0.035 & 0.905 \\ ALL & 1,997,095 & 0.932 & 0.973 & 0.093 & 0.734 & 0.868 & 0.040 & 0.927 \\ \hline \end{tabular}
\end{table} 
Table 2: Fractional agreement, probability of detection (POD), false-alarm ratio (FAR), and hit rate (HR) scores for clear-sky and cloudy-sky conditions of AGRI cloud mask products over the TP during the periods June, July and August 2020. In the statistics, MODIS cloud mask results were used as a benchmark. As shown in Figure 2, compared with the spatiotemporally collocated cloud detection results of MODIS, AGRI could identify clear and cloudy pixels with high agreement, showing good performance. Over the TP area, it was found that compared to the MODIS 1-km cloud mask, the fractional agreement of AGRI 4-km cloud mask was 0.932 for cloudy conditions. For clear-sky conditions, the fractional agreement was 0.734. However, there were distinct differences for the \"probably clear\" and \"probably cloudy\" scenes. This phenomenon is consistent with the result of the full-disk comparison [31]. These differences can mainly be attributed to the two totally different theoretical methodologies used by AGRI and MODIS for identifying \"probably clear\" and \"probably cloudy\" pixels. The MODIS Collection 6 cloud mask algorithm uses the final cloud mask confidence value based on three thresholds, as earlier mentioned (Section 2.1). In contrast, the current cloud detection algorithm for GEO satellite imagers uses spatial uniformity and two cloudy/clear restoral tests to identify \"probably clear\" and \"probably cloudy\" samples, which are closely linked to the results of neighbor pixels [31]. The TP region statistical results of the cloud mask comparison for the three months of collocated samples are presented in Table 2. The fractional agreement, POD, FAR, and HR scores of AGRI cloud mask performance were examined, and the results are separated by clear and cloudy FOVs as determined by MODIS in columns 3-9 of Table 2. Here, collocated MODIS cloud detection results were used as a benchmark.