## 2 Materials and Methods
### Study Area and Datasets
#### 2.1.3 Satellite-Based Latent Heat Flux Products  
We evaluated six satellite-based products during 2002-2015 in this study, including Global Land Surface Satellite (GLASS) LE product, FLUXCOM LE product, Penman-Monteith-Leuning V2 (PML_V2) LE product, Global Land Evaporation Amsterdam Model datasets (GLEAM) LE product, Breathing Earth System Simulator (BESS) LE product, and Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD16) LE product. To evaluate the accuracy of these products, we resampled spatially these products into 0.05 degree using bilinear method and aggregated daily LE into 8-day mean values. Table 2 summarized the detailed information of these LE products.  
1. GLASS LE product  
GLASS LE product version 4.0 is a merged LE product using Bayesian model averaging (BMA) method to merge five process-based algorithms [32]. The five algorithms include the MOD16 algorithm, the revised remote-sensing-based Penman-Monteith LE algorithm, the Priestley-Taylor-based LE algorithm, the modified satellite-based Priestley-Taylor LE algorithm and the semi-empirical Penman LE algorithm. The forcing data include the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) meteorological datasets provided by Global Modeling and Assimilation Office (GMAO), and GLASS other products [albedo, LAI, Normalized Difference Vegetation Index (NDVI), and fraction of absorbed photosynthetically active radiation (FPAR)] from Advanced Very High Resolution Radiometer (AVHRR) data. The GLASS LE product version 4.0 used in our study, with a 0.05\({}^{\circ}\) spatial resolution and 8-day temporal resolution.  
2. FLUXCOM LE product  
The FLUXCOM LE product with a 0.0833\({}^{\circ}\) spatial resolution and 8-day temporal resolution was produced from machine learning methods driven by remote sensing data [18]. This LE product was estimated exclusively from MODIS satellite data, including daytime and nighttime land surface temperature, land cover, FPAR and bidirectional reflectance distribution function (BRDF)-corrected reflectances.  
3. PML_V2 LE product  
PML_V2 (PML version 2.0) LE product was produced based on a coupled diagnostic biophysical model. The input datasets include the Global Land Data Assimilation System (GLDAS) meteorological data and the LAI, albedo, and emissivity from MODIS. The  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Site** & **Location** & **Land Cover Types** & **Elevation (m)** & **Period** \\ \hline Daxing1 (DX1) & 39.53\({}^{\circ}\) N, 116.25\({}^{\circ}\) E & Mixed forest & 30 & 2005–2006 \\ Daxing2 (DX2) & 39.62\({}^{\circ}\) N, 116.43\({}^{\circ}\) E & winter wheat/maize and vegetables & 20 & 2008–2010 \\ Guantao (GT) & 36.52\({}^{\circ}\) N, 115.13\({}^{\circ}\) E & winter wheat/maize and cotton & 30 & 2008–2010 \\ Huailai (HL) & 40.35\({}^{\circ}\) N, 115.79\({}^{\circ}\) E & maize & 480 & 2013–2014 \\ Miyun (MY) & 40.63\({}^{\circ}\) N, 117.32\({}^{\circ}\) E & orchard and maize & 350 & 2008–2010 \\ Yucheng (YC) & 36.83\({}^{\circ}\) N, 116.57\({}^{\circ}\) E & Warmer temperate dry farming cropland & 28 & 2002–2007 \\ \hline \end{tabular}
\end{table}
Table 1: Summary of the 6 flux tower sites used in this study, including the site name, location, land cover types, elevation and period.  
PML_V2 datasets provide gross primary product (GPP), vegetation transpiration (Ec), soil evaporation (Es), vaporization of intercepted rainfall (Ei) and ET_water [30; 51]. The PML_V2 LE product used in this study refers to the sum of the Es, Ei, and Ec, and it has a temporal resolution of 8 days and a spatial resolution of 0.05\({}^{\circ}\).