This dataset analyzed the uncertainty of six state-of-the-art fire emission products and merged them using the Triangular Cap Method (TCH) to generate a new global fire emission dataset, FiTCH. The FiTCH dataset provides global annual carbon emissions from fires with a spatial resolution of 0.1 degrees from 2001 to 2021. The unit of carbon emissions is gigagrams of carbon per pixel (Gg C). The stacked grid data consists of 21 bands, each representing a year since 2001. This dataset emphasizes the importance of forest fire monitoring and management for effectively mitigating climate change and protecting ecosystems
The Global Fire Assimilation System (GFAS), Rapid Fire Emissions Dataset (QFED), Global Fire Emissions Database (GFED), National Center for Atmospheric Research (NCAR) Fire Inventory (FINN), Fire Energy and Emissions Study (FEER), and data from Xu et al. (2021)
Compare and analyze six types of data using the triangular hat method.
The results indicate that satellite products such as the Global Fire Assimilation System (GFAS), Rapid Fire Emission Dataset (QFED), and Global Fire Emission Database (GFED) have lower uncertainty in fire emissions, while data from the National Center for Atmospheric Research (NCAR) Fire Inventory (FINN), Fire Energy and Emissions Study (FEER), and Xu et al. (2021) have higher uncertainty. The proposed FiTCH dataset has the lowest uncertainty, with an average annual fire emission of 1978.47 Tg C from 2001 to 2021
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.FIGSHARE.DB6694.2024
10.5194/essd-2023-150, 2023
