Development, validation, and application of a land surface reflectance and albedo dataset derived from Himawari-8/9

Geostationary meteorological satellites such as Himawari-8/9 provide unprecedented high-frequency observations that enable detailed monitoring of land surface reflectance and albedo, which are key variables for terrestrial ecosystem and surface energy/carbon cycle studies. In this study, we will introduce our current status of development, validation, and application of land surface reflectance and albedo dataset derived from Himawari-8/9 observations. Surface reflectance was estimated from Himawari-8/9 measurements using the publicly available 6SV radiative transfer model and evaluated across low-mid-high latitudes using MODIS data. Surface albedo was derived using a standard broadband albedo algorithm, and its performance was assessed using a large number of validation sites distributed across full-disk spatial domains. The results demonstrate stable and physically consistent retrievals over diverse land cover and atmospheric conditions. We further present several application examples using the established datasets, including monitoring of vegetation dynamics in tropical rainforests, phenology monitoring as the detection of leaf flushing and senescence, and the detection of rapid albedo changes associated with anthropogenic disturbances in cropland areas. These examples highlight the advantages of geostationary satellite observations for capturing diurnal to sub-seasonal variability in land surface properties. The presented datasets provide a valuable foundation for advancing studies of terrestrial ecosystem processes, land–atmosphere interactions, and surface energy and carbon exchanges using geostationary satellite observations.