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Abstract The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO₂and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite‐based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite‐based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite‐based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high‐quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite‐ and model‐based AGB estimates. We suggest the carbon‐modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation. 

Abstract While woody root structures, such as bald cypress (Taxodium distichum) “knees,” can act as conduits of methane (CH₄), little has been done to explain variation from this flux pathway. We captured spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH₄from knees, and built empirical models to predict the contribution of knees to net CH₄fluxes. Knee and soil CH₄fluxes were measured across seasons within the lower Mississippi Alluvial Valley in a main channel (semi‐permanently flooded), side channel (seasonally flooded), and a reservoir edge (artificially flooded). Knees were a net source of CH₄across all seasons, even during periods of soil CH₄uptake. During periods of high knee CH₄efflux, fluxes varied across the knee surface, decreasing with height from the ground. Knee CH₄fluxes at the main and side channels decreased during a severe drought and increased ∼ ten‐fold in summer and two‐fold in winter following flooding events. At the reservoir edge, knee fluxes differed between the controlled draw up and draw down at the same water level, likely due to differences in temperature and oxygen availability. Knee CH₄fluxes were positively correlated with water level (measured from subsurface wells, above ∼−70 cm in the soil profile) and subsurface temperature, but the strength of the relationships differed across geomorphic positions. Cypress knees appear to be an important contributor to wetland CH₄efflux and accounting for the density of knees is needed to upscale their fluxes and better understand their ecosystem contribution. 

Abstract This paper reviews the current state of high‐resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high‐resolution remote sensing using visible, near‐infrared, thermal‐infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio‐geo‐physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). Still, the state‐of‐the‐science products have their challenges and limitations, which we detail across data, retrieval algorithms, and applications. We describe the roles of these data in advancing 10 application areas: drought assessment, food security, precision agriculture, soil salinization, wildfire modeling, dust monitoring, flood forecasting, urban water, energy, and ecosystem management, ecohydrology, and biodiversity conservation. We discuss that future scientific advancement should focus on developing open‐access, high‐resolution (3–30 m), sub‐daily SM and ET products, enabling the evaluation of hydrological processes at finer scales and revolutionizing the societal applications in data‐limited regions of the world, especially the Global South for socio‐economic development.