Amazonia Wetland Methane Emission Decrease in 2023: Seasonal Forecasting of Global Wetlands Highlights Monitoring Targets in Critical Ecosystems

作者：Colin A. Quinn, Thomas Colligan, Eric J. Ward, James D. East, Yuna Lim, Eunjee Lee, Randal D. Koster, Benjamin Poulter · 发表于：Journal of Advances in Modeling Earth Systems · 年份：2025 · DOI：10.1029/2025ms005510 · 被引用次数：3 · 研究领域：Peatlands and Wetlands Ecology、Atmospheric and Environmental Gas Dynamics、Science and Climate Studies

Abstract In 2023, atmospheric methane (CH 4 ) saw a decrease in the annual growth rate following record increases from 2020 to 2022. Recent changes in CH 4 remain difficult to quantify due to delays in near‐real‐time (NRT) carbon cycle estimates. However, NRT models and subseasonal‐to‐seasonal (S2S) forecasting can provide the opportunity to analyze ongoing climate events, leading to a deeper understanding of the methane cycle. We applied the Lund‐Potsdam‐Jena Earth‐Observation‐SIMulator (LPJ‐EOSIM) to investigate methane emissions in 2023, focusing on a short‐term case study using S2S forecasts to capture wetland methane dynamics during the 2023 El Niño‐related drought in Amazonia. We modeled a 2.64 ± 5.73 Tg CH 4 decrease in global wetland methane emissions from 2022 to 2023 using an ensemble of four climate driver data sets, corresponding to ∼0.95 ppb (2.77 ppb/Tg CH 4 ), accounting for 29% of the −3.33 ppb change in atmospheric methane annual growth rate. In 2023, LPJ‐EOSIM showed tropical wetland (90°S–30°N) emissions decreased by 4.47 ± 4.79 Tg CH 4 , with Amazonia accounting for 68% of this reduction (3.05 ± 2.40 Tg CH 4 ). Meanwhile, emissions across northern latitudes (>30°N) increased by 1.83 ± 1.21 Tg CH 4 , partially offsetting the large tropical decrease. We show that the NRT LPJ‐EOSIM coupled with S2S forecasts could help forecast these anomalies in Amazonia, with reliable regional lead times at 3–5 months when forecasts were initialized following the wet‐to‐...