# Preface: Land Surface Processes and Interactions--From HCMM to Sentinel Missions and Beyond
## 2 Recent Advances in Monitoring Land Surfaces and Interactions
### Surface Energy Fluxes  
The GEWEX LandFlux evaluation [11] indicates various systematic errors (e.g., induced by different considerations of model structures/physical processes) in the existing evaporation models, and it calls for caution in using a single model for any large-scale evaluation of the water cycle (e.g., components of which are mainly produced/investigated separately). Similar conclusions were also derived by the GEWEX radiative flux assessment, which attributes the patterns of disagreement among the flux products to ancillary data differences (e.g., atmospheric temperature-humidity, surface temperature, aerosols, etc.). The aforementioned discrepancy issues can be further exaggerated at the regional scale, where the appropriate land surface parameterization may differ dramatically over different biomes and climates [12; 13; 14]. The following papers in this special issue discussed some of these challenges. [PERSON] et al. [15] introduced a Digital Surface Model (DSM) in a Computational Fluid Dynamics (CFD) Model to reproduce 3D wind fields, and to invert them for retrieving a spatialized surface roughness length for momentum (\(Z_{0m}\)). It was found that The DSM-CFD approach can estimate the roughness length well, similar to Brutsaert-based models [16], according to the estimated heat fluxes at the footprint scale. They claimed that for regional application, the likely uncertainty of the roughness information will be significant, as most NWP (Numerical Weather Prediction) models use land cover classification combined with phenological data to estimate the roughness length. To account for the impact of topography on the spatial distribution of the solar radiative budget, [PERSON] et al. [17] used the observed surface and atmosphere properties and topography to derive high temporal and spatial resolution solar radiative fluxes over the Tibetan Plateau (i.e., daily at 1 km resolution). The validation showed that, although the solar radiation estimates are satisfying in clear sky conditions, the algorithm is less reliable under cloudy sky conditions. Furthermore, it was found that the albedo product used has a too coarse temporal resolution and is therefore not accurate enough over rugged terrain. The topography also controls the distribution of land surface temperature (LST), as well as the relationship between LST and near-surface air temperature (Ta, 1.5-2 m above surface). [PERSON] et al. [18] parameterized the physiographic variables based on the terrain relief into a Ta estimation algorithm using both Terra and Aqua MODIS LST. Before taking into account the physiographic features, they concluded that the Terra nighttime LST has a strong linear relationship with Ta, especially for flat terrain areas, while in mountainous areas the relationship differed significantly from a simple linear correlation. After considering the topographic effect, as well as seasonal vegetation cover, altitudinal gradient, and the ambient absolute humidity, the accuracy of deriving Ta from LST was substantially improved. These results indicated that the relevant environmental factors must be considered when interpreting the spatiotemporal variation of the surface energy flux over complex topography. Aerosol Optical Depth (AOD) is of importance for understanding the Earth radiation budget. [PERSON] et al. [19] investigated the sensitivity of AOD to aerosol vertical profile and type, using the MODIS collection 6 algorithm over land. The results show that the AOD retrieval is highly sensitive to aerosol vertical profile and type. Errors in aerosol type assumption in the algorithm can lead to errors of up to 8% in the AOD retrieval, while the interplay effect can contribute to errors over 6%. They concluded that more attention should be paid to the case of the air pollutions caused by forest fires or extreme dust events, in order to improve the AOD retrieval. The evaporation flux over water bodies can be influenced by water salinity significantly, as salinity affects the density of water and the latent heat of vaporization.