###### Abstract  
The Tibetan Plateau (TP) has profound thermal and dynamic influences on the atmospheric circulation, energy, and water cycles of the climate system, which make the clouds over the TP the forefront of atmospheric and climate science. However, the highest altitude and most complex terrain of the TP make the retrieval of cloud properties challenging. In order to understand the performance and limitations of cloud retrievals over the TP derived from the state-of-the-art Advanced Geosynchronous Radiation Imager (AGRI) onboard the new generation of Chinese Geostationary (GEO) meteorological satellites Fengyun-4 (FY-4), a three-month comparison was conducted between FY-4A/AGRI and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) pixel-level retrievals. For cloud detection, the AGRI and MODIS cloud mask retrievals showed a fractional agreement of 0.93 for cloudy conditions and 0.73 for clear scenes. AGRI tended to miss lower CTH clouds due to the lack of thermal contrast between the clouds and the surface of the TP. For cloud top height retrievals, the comparison showed that on average, AGRI underestimated the CTH relative to MODIS by 1.366 \(\pm\) 2.235 km, and their differences presented a trend of increasing with height. Fengyun-4A; AGRI; MODIS; cloud mask; cloud top height; the Tibetan Plateau 2021 13 1418 122  
and a huge natural barrier [12; 13; 14; 15; 16; 17]. These factors make the cloud regimes over the Tibetan Plateau a link between the subsystems of regional weather and global climate. The diurnal variation of summer clouds over the TP not only has a great influence on local convection and precipitation processes, but is also closely related to floods in the Yangtze River Basin of China, the Asian summer monsoon, and the large scale climate regime in the Northern Hemisphere [13; 16; 18]. Due to the harsh natural condition of the Tibetan Plateau, few ground-based remote sensing or in situ aircraft observations of clouds have been carried out. Since the beginning of the satellite meteorology era, especially the advent of China's Fengyun-2, Fengyun-3 series satellites, Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra satellite, and the A-Train constellation, the ability to observe clouds over the TP has been greatly developed. In addition, the earliest satellite dataset, the International Satellite Cloud Climatology Project (ISCCP) products, also provide important information of the clouds over the TP [11]. The A-Train constellation, integrating passive remote sensors such as MODIS onboard an Aqua satellite with active remote sensors including Cloudsat and Cloud-Aerosol lidar and Infrared Pathfinder Satellite Observations (CALIPSO) provides us with a much more refined picture of clouds. The A-train satellite constellation, which has been in operation for more than ten years, is a successful way to observe clouds from multiple perspectives [19]. In recent years, many unique features and the role of clouds over the TP have been revealed from satellite observations, most of which are based on the measurements of MODIS/Terra, MODIS/Aqua, and Cloudsat/CALIPSO [10; 11; 20; 21; 22]. However, the Terra, Aqua, Cloudsat, and CALIPSO satellites are sun-synchronous satellites with low temporal resolution. They can only cross twice a day over the same area, which prohibits them from capturing the diurnal variations of clouds that vary greatly both spatially and temporally, especially in summer [23; 24]. A sufficiently high temporal resolution is required to study the diurnal changes of the clouds that seriously affect the energy budget of the Earth [23; 25; 26; 27]. In terms of temporal resolution, satellites in geostationary (GEO) orbit have an unquestionable advantage. They can continuously observe the same area, and this is undoubtedly extremely valuable for studying and monitoring clouds and their daily cycle.