Kok Jasper F, Adebiyi Adeyemi A, Albani Samuel, Balkanski Yves, Checa-Garcia Ramiro, Chin Mian, Colarco Peter R, Hamilton Douglas S, Huang Yue, Ito Akinori, Klose Martina, Leung Danny M, Li Longlei, Mahowald Natalie M, Miller Ron L, Obiso Vincenzo, García-Pando Carlos Pérez, Rocha-Lima Adriana, Wan Jessica S, Whicker Chloe A
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Department of Environmental and Earth Sciences, University of Milano-Bicocca, Milano, Italy.
Atmos Chem Phys. 2021;21(10):8127-8167. doi: 10.5194/acp-21-8127-2021. Epub 2021 May 27.
Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.
尽管从质量上看，沙漠尘土是地球大气中含量最为丰富的气溶胶，但大气模型仍难以准确呈现其时空分布。这些模型误差部分源于在粗分辨率模型中模拟沙尘排放以及精确表征沙尘微观物理特性时存在的根本困难。在此，我们通过开发一种新方法来减轻这些问题，该方法能更好地呈现全球沙尘循环。我们提出了一个分析框架，利用反演建模将一组全球模型模拟结果与沙尘粒径分布、消光效率及区域沙尘气溶胶光学厚度的观测约束条件相结合。然后，我们将反演模型结果与沙尘地表浓度和沉降通量的独立测量值进行比较，发现相对于当前北半球沙尘循环的模型模拟结果，误差降低了约一半。反演模型结果显示，在沙尘较少的南半球，改进幅度较小，这很可能是因为反演模型中使用的模型模拟和观测约束都不够准确。在全球范围内，我们发现几何直径达20微米的沙尘（PM）排放通量约为每年5000太克，这比大多数模型所考虑的要大。需要如此大的PM沙尘通量才能与显示大气中粗沙尘大量负荷的观测约束条件相匹配。我们获得了按季节和粒径解析的沙尘排放、垂直积分负荷、沙尘气溶胶光学厚度、（地表）浓度以及干湿沉降通量的网格化数据集。由于我们的结果表明该数据集比当前的模型模拟结果和MERRA - 2沙尘再分析产品更准确，因此可用于改进对沙尘对地球系统影响的量化。
