###### Abstract
[35] pointed out that the difficulty in characterizing cloud observation uncertainties is compounded by their strong regional dependence. The Tibetan Plateau has the highest altitude and most complex terrain in the world [18], which will make cloud retrieval more challenging, resulting in the overall evaluation results of these cloud products not applicable to TP regions. In addition, considering the influence of observation geometry, FY-4/AGRI, located at 104.7\({}^{\circ}\)E, with the capability of providing a complete image of the TP, has an advantage over Himawari/AHI, located at 140.7\({}^{\circ}\)E, in observing the TP and clouds above it. The Himawari/AHI viewing zenith angle (VZA) of the pixels on the eastern flank of the TP reaches over 50\({}^{\circ}\), and a large area in the western part of the TP is beyond its scanning range. Consequently, the cloud properties obtained from FY-4A/AGRI are very valuable for the observation and study of clouds in this area. So far, the performance of pixel-level cloud properties derived from FY-4A/AGRI over the TP has not been evaluated. Therefore, it is necessary to verify and understand the performance and limitations of AGRI cloud products over the TP based on the FYGAT algorithm to ensure the correct interpretation of the existing and future cloud datasets obtained from the measurements of the FY-4 series GEO satellite. In this context, we investigated the performance of the AGRI cloud mask and cloud-top height over the TP by comparing it with the coincident cloud retrievals of MODIS. In this paper, an accurate and computationally efficient collocation process was developed to facilitate direct comparisons of the AGRI and MODIS level-2 cloud retrievals. We also discuss the impacts of the TP's complex topography on the comparison results. The rest of this paper is organized as follows. A description of the AGRI and MODIS cloud retrievals is provided in Section 2. The collocation methodology and algorithm developed for comparison is described in Section 3, followed by a comparison method. The results of three months of the TP collocated AGRI and MODIS quantitative comparisons of cloud mask and cloud top height are presented in Section 4. A discussion about the cloud retrievals' performance distribution and the impacts of the TP's complex topography on the comparison results is given in Section 5. Conclusions are then presented in Section 6. Moderate Resolution Imaging (MODIS) and Advanced Geosynchronous Radiation Imager (AGRI) Measurements  
The primary objective of this study was to assess the performances of cloud retrieval over the TP region from AGRI flown on the FY-4A platform. We compared three months (from 1 June to 31 August 2020) of collocated AGRI and MODIS pixel-level cloud mask (CM) and cloud top height (CTH) products over the area, 25\({}^{\circ}\)N-45\({}^{\circ}\)N, 70\({}^{\circ}\)E\(\sim\)105\({}^{\circ}\)E, following the definition of the TP region by [PERSON] et al. [39]. Due to significant differences in the spatial and temporal sampling between AGRI and MODIS, it is necessary to collocate cloud products from these two instruments. Therefore, a collocation algorithm was designed to be computationally efficient and accurate, allowing for rapid identification of the coincident MODIS and AGRI observations. Cloud mask and cloud top height are crucially important and fundamental cloud products. Identifying cloud pixels from background environment, known as cloud detection or cloud mask, is fundamental and critical for optical remote sensing and for subsequent accurate image analysis [31; 40; 41]. Generally, the cloud mask algorithm lies at the top of the data processing chain and must be versatile enough to satisfy the needs of many applications [42]. Regardless of how sophisticated the new remote sensors and their applications become, cloud mask is usually the first processing step required [43]. Cloud top height is made available to all subsequent algorithms that require knowledge of the vertical extent of the clouds.