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Investigating permafrost carbon dynamics in Alaska with artificial intelligence

November 16, 2023

Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integrates in-situ measurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO2), and methane flux (CH4)—with high precision and minimal loss (i.e. ALTRMSE: 1.327 cm [1969–2022]; CO2RMSE: 0.697 µmolCO2m−2s−1 [2003–2021]; CH4RMSE: 0.715 nmolCH4m−2s−1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Publication Year 2023
Title Investigating permafrost carbon dynamics in Alaska with artificial intelligence
DOI 10.1088/1748-9326/ad0607
Authors Bradley Gay, Neal Pastick, Andreas Zufle, Amanda Armstrong, Kimberly Miner, J.J. Qu
Publication Type Article
Publication Subtype Journal Article
Series Title Environmental Research Letters
Index ID 70250271
Record Source USGS Publications Warehouse
USGS Organization Earth Resources Observation and Science (EROS) Center