A High-Resolution, Long-Term Global Radar-Based Above-Ground Biomass Dataset from 1993 to 2020

Abstract. Understanding global carbon dynamics and budgets under climate change, land-use shifts, and increasing disturbances re- mains challenging due to the limitations of existing coarse spatial resolution and short-term or discontinuous biomass datasets. In this study, we generated a new global annual above-ground biomass carbon (AGC) dataset at 8 km spatial resolution from 1993 to 2020. This dataset is derived from satellite radar backscatter data and integrates vegetation and climate information, such as tree cover, tree density, and background climate data, to enhance the accuracy of global AGC mapping. Our dataset estimates an average global above-ground carbon stock of 378 PgC, aligning with other global estimates. We observe a slight gross increase of 1.18 PgC in global vegetation above-ground biomass carbon stocks from 1993 to 2020, with relatively stable variation. This reflects a balance between above-ground biomass carbon gains and losses across different biomes. Temperate and boreal forests are the primary contributors to global vegetation above-ground biomass carbon gains from 1993 to 2020, with increases of 0.4 and 0.5 PgC, respectively. In contrast, gross above-ground biomass carbon losses are predominantly observed in global tropical forests (-10.7 PgC) and global shrublands (-1.0 PgC). This suggests non-forest vegetation may offset the large above-ground biomass losses in tropical forests. Notably, El Niño events in 2015/16 triggered significant pantropical AGC losses of approximately -2.86 PgC, and regions with reported tree mortality events (Hammond et al., 2022) exhibited local AGC density declines of -0.34 MgC/ha. This long-term, temporally continuous, and moderate-resolution dataset provides a valuable resource for understanding biomass carbon dynamics and integrating these processes into Earth System Models. The AGC dataset is openly accessible, alongside with this manuscript.