Quantifying pyroconvective injection heights using observations of fire energy: sensitivity of spaceborne observations of carbon monoxide
Quantifying pyroconvective injection heights using observations of fire energy: sensitivity of spaceborne observations of carbon monoxide
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DOI：
10.5194/acp-15-4339-2015
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发表时间：
2015-01-01
影响因子：
6.3
通讯作者：
Deeter, M. N.
中科院分区：
文献类型：
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作者：
Gonzi, S.;Palmer, P. I.;Deeter, M. N.
我们利用NASA中分辨率成像光谱仪(MODIS)对活跃火区和火辐射功率(FRP)的观测，结合参数化的烟羽上升模型，估计了2006年期间生物质燃烧的喷射高度。我们在GEOS-CHEM(戈达德地球观测系统化学)大气化学输送模式中使用这些喷射高度来垂直分布生物质燃烧排放的一氧化碳(CO)，并研究由此产生的大气分布。2006年，我们使用了超过50万次玻璃钢和火区观测作为烟羽上升模型的输入。结果表明，对流热流密度一般在1~100kWm(-2)范围内，活动火区一般在0.001~100ha范围内，但极少数情况下对流热流密度可超过500kWm(-2)。由此产生的喷注高度具有倾斜的概率分布，大约80%的喷注留在局部边界层内，偶尔喷注高度超过8公里。我们没有发现FRP推断的地面对流热通量与由此产生的喷射高度之间的强烈相关性，即使在对流热通量和活跃火区较大的情况下，环境条件也经常成为快速垂直混合的障碍。我们也没有发现潜在的烧毁植被类型和喷射高度之间的牢固关系。我们发现，使用MODIS推断的喷射高度(MODISINJ)计算的CO柱与排放到边界层的控制计算通常有-9%到+6%的差异，其中在排放点的差异通常最大。在应用MOPITT(对流层污染测量)v5场景相关平均核之后，我们发现我们对喷射高度剖面的选择不那么敏感。MOPITT和模型CO柱之间的差异(最大偏差接近50%)，主要是由于排放清单中的不确定性，比喷射高度引入的差异要大得多。我们表明，包括FRP的真实日变化(下午达到峰值)或考虑亚网格尺度的排放误差不会改变我们的主要结论。最后，我们使用了受MOPITT CO廓线约束的贝叶斯最大后验估计方法来估计CO排放，但由于模型与MOPITT之间存在固有的偏差，我们发现对由此产生的排放估计几乎没有影响。利用MOPITT的全球CO观测(或任何目前的大气空间测量)研究热对流在大气中气体和颗粒分布中的作用仍然存在很大的误差，但有一小部分大火和有利的环境条件除外，这将导致在全球范围内进行任何分析时出现偏差。
We use observations of active fire area 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 (Goddard Earth Observing System Chemistry) 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 area observations as input to the plume rise model. We find that convective heat fluxes and active fire area typically lie in the range of 1-100 k W m(-2) and 0.001-100 ha, respectively, although in rare circumstances the convective heat flux can exceed 500 k W m(-2). The resulting injection heights have a skewed probability distribution with approximately 80% of the 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 active fire area 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 (MODISINJ) are typically -9 to +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 (Measurement of Pollution in the Tropo-sphere) 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 approximate to 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 the distribution of gases and particles in the atmosphere using global MOPITT CO observations (or any current spaceborne 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.