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Abstract
Abstract. Proper quantification of the aerosol vertical height is essential to constrain the atmospheric distribution and lifetime of aerosols, as well as their impact on the environment. We use globally distributed, daily averaged measurements of aerosol stereo heights of fire aerosols from the Multi-angle Imaging SpectroRadiometer (MISR) to understand the aerosol distribution. We also connect these results with a simple plume rise model and a new multi-linear regression model approach based on daily measurements of NO2 from OMI and CO from MOPITT to understand and model the global aerosol vertical height profile over biomass burning regions. First, plumes associated with the local dry-burning season at midlatitudes to high latitudes frequently have a substantial fraction lofted into the free troposphere and in some cases even the stratosphere. Second, plumes mainly associated with less-polluted regions in developing countries and heavily forested areas tend to stay closer to the ground, although they are not always uniformly distributed throughout the boundary layer. Third, plumes associated with more serious loadings of pollution (such as in Africa, Southeast Asia and northeast China) tend to have a substantial amount of smoke transported uniformly through the planetary boundary layer and up to around 3 km. Fourth, the regression model approach yields a better ability to reproduce the measured heights compared to the plume rise model approach. This improvement is based on a removal of the negative bias observed from the plume model approach, as well as a better ability to work under more heavily polluted conditions. However, over many regions, both approaches fail, requiring deeper work to understand the physical, chemical and dynamical reasons underlying the failure over these regions.
Highlights
Over the past few decades, there has been an increasing amount of research into the spatial and temporal distribution of atmospheric aerosols (Achtemeier et al, 2011; Cohen et al, 2017, 2018)
By choosing both regression models that represent the format of the plume rise model and those that do not, but are instead based on additional information from MOPITT and OMI, we are thereby including these data in a way that is consistent with the underlying science and without bias
If we look across Africa as a whole, we find that the underestimate is on average 52 %, a finding which deviates more from the measured aerosol vertical distribution than previous global studies (Val Martin et al, 2018) as well as those over Southeast Asia
Summary
Over the past few decades, there has been an increasing amount of research into the spatial and temporal distribution of atmospheric aerosols (Achtemeier et al, 2011; Cohen et al, 2017, 2018). This has been in part because of the impacts that aerosols have on clouds, radiation, the atmospheric energy balance and climate, human health, and ecosystems, among other aspects (Cohen, 2014; Tao et al, 2012; Ramanathan et al, 2007; Ming et al, 2010). Understanding the vertical distribution over the source regions (Nelson et al, 2013) of aerosols and how this may change over time is absolutely critical for our being able to better constrain the environmental and atmospheric impacts
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