Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

El Masri, Bassil; Xiao, Jingfeng

doi:10.1029/2024jg008305

Title: Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

Journal Article · 26 December 2024 · Journal of Geophysical Research. Biogeosciences

DOI: https://doi.org/10.1029/2024jg008305 · OSTI ID:2497305

^[1]; Xiao, Jingfeng ^[2]

Murray State University, KY (United States); Murray State University
University of New Hampshire, Durham, NH (United States)

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 CO₂ and 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. Furthermore, 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.

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Research Organization:: Murray State University, KY (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0022228

OSTI ID:: 2497305

Report Number(s):: DOE-MSU--SC0022228

Journal Information:: Journal of Geophysical Research. Biogeosciences, Journal Name: Journal of Geophysical Research. Biogeosciences Journal Issue: 1 Vol. 130; ISSN 2169-8953

Publisher:: American Geophysical UnionCopyright Statement

Country of Publication:: United States

Language:: English

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54 ENVIRONMENTAL SCIENCES
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