A global fire emission dataset using the three-corner hat method (FiTCH)

Anthropogenic carbon emissions induce rising temperatures and climate change. Fire carbon emissions contribute to the accumulation of atmospheric CO2 and affect climate change. It is crucial to accurately monitor the dynamics of global fire emissions for fire management and climate change mitigation. This study merged six commonly used satellite-based fire emission products (the GFED 4.1s, GFAS 1.2, QFED 2.5, FINN 2.5, FEER 1.0, and Xu et al. (2021)) using the three-corner hat method (TCH) (Premoli and Tavella, 1993) and produced a new global fire emission dataset, FiTCH. The FiTCH dataset provides global annual fire carbon emissions from 2001 to 2021 at the spatial resolution of 0.1 degree. The unit of carbon emissions is gigagram carbon (Gg C) per pixel. There are 21 bands in the stacked raster data, where each band indicates a year since 2001. Note: The GFED 4.1s data were from the Global Fire Emissions Database (GFED) (van der Werf et al., 2017). The GFAS 1.2 data were from the Global Fire Assimilation System (GFAS) (Kaiser et al., 2012). The QFED 2.5 data were from the Quick Fire Emissions Dataset (QFED) (Koster et al., 2015). The FINN 2.5 data were from the Fire INventory from National Center for Atmospheric Research (NCAR) (FINN) (Wiedinmyer et al., 2023). The FEER 1.0 data were from the Fire Energetics and Emissions Research (FEER) (Ichoku and Ellison, 2014). The Xu et al. (2021) global fire emission data came from "Changes in global terrestrial live biomass over the 21st century" published in Science Advance. References Ichoku, C., Ellison, L., 2014. Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements. Atmospheric Chemistry and Physics 14, 6643–6667. https://doi.org/10.5194/acp-14-6643-2014 Kaiser, J.W., Heil, A., Andreae, M.O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M.G., Suttie, M., van der Werf, G.R., 2012. Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences 9, 527–554. https://doi.org/10.5194/bg-9-527-2012 Koster, R.D., Darmenov, A.S., da Silva, A.M., 2015. The Quick Fire Emissions Dataset (QFED): Documentation of Versions 2.1, 2.2 and 2.4 (No. NASA/TM-2015-104606 /Vol. 38). Premoli, A., Tavella, P., 1993. A revisited three-cornered hat method for estimating frequency standard instability. IEEE Transactions on Instrumentation and Measurement 42, 7–13. https://doi.org/10.1109/19.206671 van der Werf, G.R., Randerson, J.T., Giglio, L., Leeuwen, T.T. van, Chen, Y., Rogers, B.M., Mu, M., Marle, M.J.E. van, Morton, D.C., Collatz, G.J., Yokelson, R.J., Kasibhatla, P.S., 2017. Global fire emissions estimates during 1997–2016. Earth System Science Data 9, 697–720. https://doi.org/10.5194/essd-9-697-2017 Wiedinmyer, C., Kimura, Y., McDonald-Buller, E.C., Emmons, L.K., Buchholz, R.R., Tang, W., Seto, K., Joseph, M.B., Barsanti, K.C., Carlton, A.G., Yokelson, R., 2023. The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications. EGUsphere 1–45. https://doi.org/10.5194/egusphere-2023-124 Xu, L., Saatchi, S.S., Yang, Y., Yu, Y., Pongratz, J., Bloom, A.A., Bowman, K., Worden, J., Liu, J., Yin, Y., Domke, G., McRoberts, R.E., Woodall, C., Nabuurs, G.-J., de-Miguel, S., Keller, M., Harris, N., Maxwell, S., Schimel, D., 2021. Changes in global terrestrial live biomass over the 21st century. Science Advances 7, eabe9829. https://doi.org/10.1126/sciadv.abe9829