## 2 Materials and Methods
### Data
#### 2.2.1 Remote Sensing Products  
FY-4A/AGRI LST  
FY-4A is the first satellite in the FY-4 series of independently developed Chinese second-generation geostationary meteorological satellites. FY-4A was the most advanced integrated atmospheric observation satellite of its time. It was launched in December 2016 and delivered in September 2017, positioned over the equator at 99.5\({}^{\circ}\) E (it later drifted to 104.7\({}^{\circ}\) E). The three-axis stabilized FY-4 series offers full disk coverage every 15 min or better (in contrast to the 30 min of FY-2), and there is an option for more frequent regional and mesoscale observation modes. The Advanced Geostationary Radiation Imager (AGRI) on FY-4A, with 14 channels, provides data that can be used to improve applications in a wide range of oceanic, land, and atmospheric monitoring activities and in forecasting extreme weather, especially typhoons and thunderstorms [12]. FY-4A LST data retrieval is based on the split-window algorithm [34] and uses two TIR channels (10.3-12.5 \(\upmu\)m). The sensitivity of the product is 0.2 K, the spatial resolution is 4 km, and the temporal resolution is up to 15 min. The product was projected using the normalized projection (NOM) and was downloaded from [[http://satellite.nsmc.org.cn/](http://satellite.nsmc.org.cn/)]([http://satellite.nsmc.org.cn/](http://satellite.nsmc.org.cn/)) (accessed on 2 April 2021). Data were stored in netCDF format.  
Himawari-8/AHI LST  
Himawari-8 is a Japanese meteorological satellite that became operational in July 2015. It is positioned over the equator at 140\({}^{\circ}\) E. The primary instrument aboard Himawari-8 is the advanced Himawari imager (AHI), which is a 16-channel multispectral imager that captures visible light and infrared images of the Asia-Pacific region. AHI is similar to AGRI, so its LST product can be used for comparison with the FY-4A LST product. The Eastern Asia and Oceania LST of the Copernicus LST version 2 datasets derived from Himawari-8 data was retrieved using the generalized split-window algorithm (GSW) for two adjacent TIR channels (10.8-13.1 \(\upmu\)m). The spatial resolution is 0.045\({}^{\circ}\), the temporal resolution is 1 h, and it was projected using WGS 1984 and downloaded from [[http://land.copernicus.eu/](http://land.copernicus.eu/)]([http://land.copernicus.eu/](http://land.copernicus.eu/)) (accessed on 2 April 2021). Data were stored in netCDF format.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Data Category** & **Data Name** & **Time Period** & **Temporal Resolution** & **Spatial Resolution** \\ \hline Remote sensing & FY-4A/AGRI LST & 1 October 2019 0 h– & 1 h & 4 km \\  & & 30 September 2019 23 h & & \\ products & Himawari-8/AHI LST & 1 October 2019 0 h– & 1 h & 0.045\({}^{\circ}\) \\  & & 30 September 2019 23 h & & \\ \cline{2-5}  & In situ measured data & 1 October 2019 0 h– & & \\  & from CMA stations & 30 September 2019 23 h & & \\ \cline{2-5}  & & 1 October 2019 0 h– & & \\ Reanalysis products & & 30 September 2019 23 h & & \\  & ERA5-Land LST & 1 October 2019 0 h– & & \\  & & 30 September 2019 23 h & & \\ \cline{2-5}  & NASA ASTER GDEM v3 & 2021 & / & 30 m \\  & China’s & 2020 & / & 30 m \\  & GlobalLand30 v2020 & & / & 30 m \\  & Geomorphic type data & 2009 & / & 1:1,000,000 \\ Auxiliary data & from IGSNRR, CAS & 2009 & / & \\  & Soil moisture data & 1 October 2019– & & \\  & retrieval from SMAP & 30 September 2019 & 1 d & 36 km \\  & NDVI data of & 22 September 2019– & & \\  & NASA VNP13A2 & 30 March 2021 & 16 d & 1 km \\ \hline \end{tabular}
\end{table}
Table 1: Datasets used in this study.