Forest Carbon Modeling Improved Through Hierarchical Assimilation of Pool-Based Measurements

IF 4.4 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Advances in Modeling Earth Systems Pub Date : 2025-03-13 DOI:10.1029/2024MS004622
Yu Zhou, Christopher A. Williams
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Abstract

Accurate assessment of forest carbon dynamics is a critical element of appraising forest-based Natural Climate Solutions. National forest inventory and analysis (FIA) data provide valuable pool-based estimates of carbon stocks, but have been underutilized to inform carbon cycle modeling for forest carbon dynamics with stand development. This study introduces a hierarchical data assimilation (HDA) framework to optimize modeling parameters by incrementally assimilating measured carbon pool data into the model. We found that most carbon stocks could be reproduced by constrained parameters after each HDA step. Using aboveground live biomass (AGB) alone in HDA was able to reproduce the AGB trajectories but introduced biases in estimating the downstream dead biomass and soil carbon pools. Assimilating dead biomass measurements narrowed the posterior space of parameter solutions and improved consistency between measured and modeled carbon dynamics. The HDA framework also reduced uncertainties on modeled carbon fluxes. Young stands were found to release less carbon when the model was informed by dead biomass compared to simulations guided by aboveground biomass alone. The remaining mismatches between modeled and FIA pool estimates could be attributed to wide uncertainty in some FIA estimates, differing definitions of functional carbon pools, and structural rigidity in the model. Together, this study underscores the importance of pool-based measurements in forest carbon modeling, which improves the model-observation fit and reduces process-model uncertainty.

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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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