Six global biomass burning emission datasets: intercomparison and application in one global aerosol model
Data sets
The quick fire emissions dataset (QFED) (https://portal.nccs.nasa.gov/datashare/iesa/aerosol/emissions/QFED/v2.4r6/) https://gmao.gsfc.nasa.gov/pubs/docs/Darmenov796.pdf
Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical (https://aeronet.gsfc.nasa.gov/new_web/download_all_v3_aod.htm https://doi.org/10.5194/amt-12-169-2019
Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements (http://feer.gsfc.nasa.gov/data/emissions/) https://doi.org/10.5194/acp-14-6643-2014
Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power (https://apps.ecmwf.int/datasets/data/cams-gfas/) https://doi.org/10.5194/bg-9-527-2012
Ability of multiangle remote sensing observations to identify and distinguish mineral dust types: Part 2. Sensitivity over dark water (https://eosweb.larc.nasa.gov/project/misr/mil3mae_table) https://doi.org/10.1029/2005JD006756
Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) (https://daac.ornl.gov/VEGETATION/guides/global_fire_emissions_v3.1.html) https://doi.org/10.5194/acp-10-11707-2010
Global fire emissions estimates during 1997–2016 (http://www.globalfiredata.org) https://doi.org/10.5194/essd-9-697-2017
The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning (http://bai.acom.ucar.edu/Data/fire/) https://doi.org/10.5194/gmd-4-625-2011