### Moderate Resolution Imaging (MODIS)  
Since the National Aeronautics and Space Administration (NASA) launched the \"Terra\" satellite in 1999 and the \"Aqua\" satellite in 2002, MODIS has become a keystone instrument and one of the most widely used satellite remote sensing platforms in the Earth Observing System (EOS) [46; 49]. MODIS measures reflected solar and emitted thermal radiation in 36 spectral channels ranging from the visible (VIS) to the infrared (IR), with a spatial resolution of 250 m (two bands), 500 m (five bands), and 1000 m (29 bands). These channels, essentially covering all of the key atmospheric bands located between 0.415 and 14.235 um, have been carefully selected to enable advanced studies of land, ocean, and atmospheric features, which provides unique spectral and spatial capabilities for retrieving cloud properties [46; 50]. MODIS cloud properties' retrieval algorithms have evolved over the past two decades [46; 49; 51; 52; 53; 54]. MODIS cloud products have been validated by comparing them with active remote sensor observations and radiance simulations [35; 55; 41; 53], and are widely used in studies of cloud macro-microphysical and optical properties [5; 10; 56; 57; 58; 59; 60]. In addition, MODIS cloud products are also used as benchmarks or truth values for the verification and evaluation of satellite cloud products and retrieval algorithms [29; 31; 61; 62; 36]. The newest MODIS reprocessing dataset of the products, Collection 6 (C6), was completed in 2014 and 2015 for Aqua and Terra, respectively. The C6 update activity has benefited greatly from being able to compare MODIS radiance data and derived products with various sensors that compose the A-Train [54]. MODIS pixel-level (level-2) cloud products are generated on a granule basis, known as MOD06 and MYD06 for Terra and Aqua, respectively. A granule consists of 5 min of data. MOD06 and MYD06 in C6 provide the cloud parameters at a 1 km spatial resolution. When we were working on this study, the MYD06 data (from June to August 2020) downloaded from the official MODIS website were incomplete, that is, there is a large amount of MYD06 data that are missing during that time period. In addition, to avoid the uncertainty of comparison due to the differences between Terra and Aqua in this study, only cloud products of MOD06 in Collection 6 were used as the benchmark to compare and validate the level-2 cloud products of FY-4A/AGRI based on the FYGAT algorithm. Cloud mask is based on the contrast between the cloud and background environment. Contrast can be defined by differing signals for individual spectral bands, spectral combinations, or temporal and spatial variations of these [49]. The MODIS cloud mask algorithm employs up to 19 spectral bands to maximize reliable cloud detection [35]. In fact, the Collection 6 cloud mask algorithm uses as many as 22 bands [42]. After a series of sequential tests on the passive reflected solar and infrared observations, a degree of clear-sky confidence is assigned to the result to assess the likelihood that clouds obstruct a given pixel. Then, final cloud mask confidence (Q) is based on three thresholds (i.e., 0.66, 0.95, and 0.99). Test results can classify cloud contamination in every pixel of data as either confident clear (Q > 0.99), probably clear (Q > 0.95), probably cloudy (Q > 0.66), or cloudy (Q \(\leq\) 0.66) [49]. Based on the comparison with three years of coincident observations, an assessment of the performance of MODIS cloud mask algorithm showed that the MODIS algorithm agrees with the combined radar and lidar from ground about 85% of the time [41]. Globally, the MODIS 1-km cloud mask and the CALIOP 1-km averaged layer product agreement is 87% for cloudy conditions for both August and February; for clear-sky conditions, the agreement is 85% (86%) for August (February) [35]. MODIS cloud top pressure (CTP) is determined using five thermal infrared bands (both day and night). The 11 \(\upmu\)m infrared window brightness temperature data are used to estimate low clouds.