High-Resolution Global land surface Albedo Component Datasets (HR-GACD) for Bare Soil, Non-photosynthetic Vegetation, and Photosynthetic Vegetation

Land surface albedo (LSA) plays a fundamental role in the terrestrial energy-water-carbon nexus, with its variability primarily driven by contributions from bare soil (SL), non-photosynthetic vegetation (NPV), and photosynthetic vegetation (PV). However, current global land surface models (LSMs) primarily rely on temporally static maps or simplified look-up tables for albedo components, which inadequately capture their spatiotemporal dynamics. While satellite-derived LSA products provide dynamic LSA observation information, they do not explicitly separate individual surface albedo components, and existing unmixing models struggle to isolate NPV impacts from bare soil backgrounds. To bridge these gaps, this study develops a generalized parameterization scheme and global albedo component datasets across three broadbands (visible, near infrared, and shortwave) and seven MODIS spectral bands. Following the mathematical form of the Ross-Thick Li-Sparse (RTLS) model, we explicitly parameterize the surface albedo components using cubic and exponential polynomial equations, incorporating the effects of soil/vegetation types, soil moisture, terrain roughness, and solar zenith angle (SZA). Furthermore, a pixel-wise optimization model refines the parameterization, enabling the generation of global gap-free albedo component maps at 500 m and 0.05° resolutions. Global site validation yields RMSEs of 0.043 for SL albedo, 0.051 for NPV albedo, and 0.029 for PV albedo, outperforming existing methods. Cross-validation indicates that the albedo components are consistent with the reference product, while preserving high spatial resolution and accounting for illumination geometry effects. Additionally, the derived maps exhibit reasonable spatiotemporal variability at both regional and global scales. Excluding the impact of NPV increases the SL albedo magnitude, thereby introducing decreases in soil net radiation by 7.80 W m⁻² (11%) over semi-arid regions. Evapotranspiration partitioning suggests that the SL albedo update helps mitigate the common overestimation of soil evaporation in drylands by improving surface energy representation. Vegetation albedo analysis underscores the critical role of illumination geometry in modeling circadian rhythms across diverse ecosystems. The open-source albedo component parameterization framework and maps will facilitate research on diurnal albedo asymmetry, water and carbon fluxes, and biophysical effects of vegetation components, with broad implications for high-resolution climate and ecohydrological modeling. The "Download all" button may not work properly due to the large data volume. The corresponding paper has been published in Remote Sensing of Environment. Codes for calculating MODIS LSA from BRDF parameters are included, along with the corresponding gridding code for converting MODIS sinusoidal projection to latitude/longitude. For additional details, please contact Dr. Aolin Jia at [e-mail].