## 5 Conclusions  
In this study, we directly compared the FY-4A LST product with in situ measured LST data and used TCA with other reanalysis products to test the authenticity of the FY-4A LST product, which has not previously been extensively validated, for accuracy. We used Himawari-8 LST for comparison. We analyzed the effects of several environmental factors on LST accuracy. We drew the following conclusions. 1. The FY-4A LST product captured the surface temperature well for Hunan Province (R = 0.893, Rho = 0.915), but it generally underestimated LST (Bias = \(-\)0.6295 \({}^{\circ}\)C) and there was a large random error (RMSE = 8.588 \({}^{\circ}\)C, ubRMSE = 5.842 \({}^{\circ}\)C); observation accuracy was worse than for Himawari-8 LST. 2. The FY-4A LST product performed better in terms of accuracy for the central-eastern area, the northern area except Dongting Lake, and the central-southern parts of Hunan Province than for other parts of the province. The greatest accuracy was for the Hengyang basin in central Hunan. Accuracy decreased in the western and southern mountainous areas and the Dongting Lake area, and accuracy was the lowest in the mountainous areas along the southern and northwestern borders. 3. When the surface temperature is high (>25 \({}^{\circ}\)C), remote sensing detection will significantly underestimate LST, and accuracy is greatly affected by topography and terrain; product accuracy decreases as elevation increases, and the change trend is basically consistent with change in elevation. FY-4A LST is most accurate when the land cover is Cultivated land or Artificial surfaces and the landform is Platform. Accuracy changes between day and night and seasonally, and decreases as land cover becomes more heterogeneous, mountain relief increases, or slope and NDVI increase; accuracy increases as soil moisture increases. FY-4A is an experimental satellite and its detection performance exceeded expectations and provided a variety of valuable observation products for China's meteorological operations. However, our evaluation found that the FY-4A LST product is not as accurate as advanced foreign satellite products, and so there is still a need to improve the performance of domestic satellite instruments and to improve the retrieval algorithm by combining environmental factors so as to improve China's meteorological detection capability. Data curation, S.T. and W.L. ; formal analysis, S.W. ; funding acquisition, Q.H. ; investigation, J.F. ; methodology, J.F., Q.H. and H.L. ; project administration, Q.H. ; resources and software, J.F., S.W., L.C. and H.S. ; writing--original draft, J.F. ; validation and writing--review and editing, H.L. All authors have read and agreed to the published version of the manuscript. This research was funded by Hunan Meteorological Bureau, grant number NO. XQKJ18A003 and NO. XQKJ22C010, and the major program of the Natural Science Foundation of Hunan province: \"Multi-source satellite remote sensing model of meso- and micro-scale severe convective weather system and its derived disasters\". Not applicable. All the data used in the study can be obtained in a public way, as described in the Data section of the article. We thank the global component of Land Service of Copernicus, the Earth Observation programme of the European Commission, and Japan Meteorological Agency for providing Himawari-8 LST product. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.