Hongzhao Wang, Jun Wang, Zishan Wang, Junyuan Chen, Jiawen Zhu, Qian Zhang. 2025: Assessment of Regional Fire Carbon Emissions during 2003-2023 Simulated by Multiple CMIP6 Models. Adv. Atmos. Sci.,
Citation: Hongzhao Wang, Jun Wang, Zishan Wang, Junyuan Chen, Jiawen Zhu, Qian Zhang. 2025: Assessment of Regional Fire Carbon Emissions during 2003-2023 Simulated by Multiple CMIP6 Models. Adv. Atmos. Sci.,

Assessment of Regional Fire Carbon Emissions during 2003-2023 Simulated by Multiple CMIP6 Models

  • Wildfires play a critical role in the Earth system, affecting climate, carbon cycling, air quality, and human livelihoods. The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides multi-model simulations of historical and future wildfire carbon emissions, yet substantial uncertainties remain. Here, we evaluate fire carbon emissions from 10 CMIP6 models over 2003–2023 using three satellite-based datasets (GFED, GFAS, QFED) across 14 sub-regions. The multi-model ensemble (MME) reproduces broad spatial patterns with a pattern correlation coefficient of 0.64 and normalized standard deviation of 1.00, but overestimates emissions in most regions, particularly the tropics, leading to inflated global totals. Only 5 out of 14 sub-regions show good agreement with observations. Seasonality is reasonably captured, with most models simulating peak fire months within ±1 month. Sensitivity analysis reveals strong regional variation in fire responses to near-surface air temperature (TAS) and surface soil moisture (SM). The MME correctly identifies TAS as the dominant driver in most high- and mid-latitudes but misrepresents the relative influence of TAS and SM in key tropical regions. Observationally, widespread declines in tropical fire emissions contribute to an overall global decrease (−0.02 PgC yr⁻2), but CMIP6 models fail to capture these trends, instead simulating spurious increases that drive unrealistic upward global trends (0.03 PgC yr⁻2). These discrepancies are largely attributed to inadequate representation of anthropogenic fire suppression and overestimated temperature sensitivity. Our results highlight the need for improved fire-process parameterizations to enhance the reliability of future projections of fire-related carbon emissions under climate change.
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