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We use observations of fire size and fire radiative power (FRP) from the NASA Moderate-Resolution Imaging Spectroradiometers (MODIS), together with a parameterized plume rise model, to estimate biomass burning injection heights during 2006. We use these injection heights in the GEOS-Chem atmospheric chemistry transport model to vertically distribute biomass burning emissions of carbon monoxide (CO) and to study the resulting atmospheric distribution. For 2006, we use over half a million FRP and fire size observations as input to the plume rise model. We find that convective heat fluxes and actual fire sizes typically lie in the range of 1–100 kW m−2 and 0.001–100 ha, respectively, although in rare circumstances the convective heat flux can exceed 500 kW m−2. The resulting injection heights have a skewed probability distribution with approximately 80% of injections remaining within the local boundary layer (BL), with occasional injection height exceeding 8 km. We do not find a strong correlation between the FRP-inferred surface convective heat flux and the resulting injection height, with environmental conditions often acting as a barrier to rapid vertical mixing even where the convective heat flux and actual fire size are large. We also do not find a robust relationship between the underlying burnt vegetation type and the injection height. We find that CO columns calculated using the MODIS-inferred injection height (MODIS-inj) are typically −9–+6% different to the control calculation in which emissions are emitted into the BL, with differences typically largest over the point of emission. After applying MOPITT v5 scene-dependent averaging kernels we find that we are much less sensitive to our choice of injection height profile. The differences between the MOPITT and the model CO columns (max bias ≈ 50%), due largely to uncertainties in emission inventories, are much larger than those introduced by the injection heights. We show that including a realistic diurnal variation in FRP (peaking in the afternoon) or accounting for subgrid-scale emission errors does not alter our main conclusions. Finally, we use a Bayesian maximum a posteriori approach constrained by MOPITT CO profiles to estimate the CO emissions but because of the inherent bias between model and MOPITT we find little impact on the resulting emission estimates. Studying the role of pyroconvection in distributing gases and particles in the atmosphere using global MOPITT CO observations (or any current space-borne measurement of the atmosphere) is still associated with large errors, with the exception of a small subset of large fires and favourable environmental conditions, which will consequently lead to a bias in any analysis on a global scale.
|Journal||Atmospheric Chemistry and Physics|
|Publication status||Published - 29 Apr 2015|
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