the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Biomass Burning Emissions Analysis Based on MODIS AOD and AeroCom Multi-Model Simulations
Abstract. We assessed the performance of 11 AeroCom models in simulating biomass burning (BB) smoke aerosol optical depth (AOD) in the vicinity of fires over 13 regions globally. By comparing multi-model outputs and satellite observations, we aim to: (1) assess the factors affecting model-simulated, BB AOD performance using a common emissions inventory, (2) identify regions where the emission inventory might underestimate or overestimate smoke sources, and (3) identify anomalies that might point to model-specific smoke emission, dispersion, or removal, issues. Using satellite-derived AOD snapshots to constrain source strength works best where BB smoke from active sources dominates background aerosol, such as in boreal forest regions and over South America and southern-hemisphere Africa. The comparison is poor where the total AOD is low, as in many agricultural burning areas or where background, non-BB AOD is high, such as parts of India and China. Many inter-model BB AOD differences can be traced to differences in model-assumed values for the mass ratio of organic aerosol to organic carbon, the BB aerosol mass extinction efficiency, and the aerosol loss-rate. The results point to the need for increased numbers of available BB cases for study in some regions, and especially to the need for more extensive, regional-to-global-scale measurements of aerosol loss rates and of detailed microphysical and optical properties; this would better constrain models and help distinguish BB from other aerosols in satellite retrievals. More generally, there is the need for additional efforts at constraining aerosol source strength and other model attributes with multi-platform observations.
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Status: open (until 12 Jul 2024)
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RC1: 'Comment on egusphere-2024-1487', Anonymous Referee #1, 21 Jun 2024
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Major:
- GFED 3.1 is very outdated and has been shown to underestimate fires, particularly small ones. I understand that that’s what was used in the multimodel study, but, at the minimum, an uncertainty analysis showing the difference between that and updated fire inventories should be included and a discussion of the limitations of GFED3.1.
- The models compared are also quite old. Specifically GEOS-Chem v9-02 is super outdated. I understand that that was what was used in the intercomparison, but the science is so outdated as to raise the question - is this comparison useful now? What is the added value of a paper like this when a lot of these fire comparisons have already been done and this study is using outdated models and fire inventories? Most, if not all, of these takeaways have been shown in other work (papers by Tina Liu, Carter et al. (2020), Pan et al. like the other cite, etc.)
- More of a discussion of MODIS AOD uncertainties would also be useful.
Minor:
- The intro should make mention of Carter et al. (2020) that looked at fire-influenced AOD in North America.
- Figure 6 would make more sense if BB was red across both MODIS and model instead of current color scheme.
Citation: https://doi.org/10.5194/egusphere-2024-1487-RC1
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