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Improved representation of the global dust cycle using observational constraints on dust properties and abundance

机译:在灰尘性质和丰度上使用观察限制改进了全局灰尘周期的表示

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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 2?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 a geometric diameter up to 20? μ m (PM 20 ) is approximately 5000?Tg?yr ?1 , which is greater than most models account for. This larger PM 20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets 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 dataset 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.
机译:尽管沙尘粉尘是地球大气层中最丰富的气溶胶,但大气模型努力准确地代表其空间和时间分布。这些模型误差是由基本困难在粗分辨率模型中模拟粉尘发射的基本困难和准确表示粉尘微手术性质。在这里,我们通过开发一种新的方法来减轻这些问题,从而产生改进的全局灰尘周期的表示。我们介绍了一个分析框架,使用逆建模来集成全球模型模拟的集合,其对灰尘尺寸分布,消光效率和区域粉尘光学深度的观测限制。然后,我们将反向模型结果与灰尘表面浓度和沉积通量的独立测量进行比较,发现误差减小了大约2的因子?相对于北半球粉尘循环的当前模型模拟。逆模型结果显示较少的尘埃南半球的改进,最有可能因为模型模拟和反向模型中使用的观察限制都不太准确。在全球范围内,我们发现灰尘的排放通量,几何直径高达20? μM(PM 20)约为5000?TG?YR?1,其大多数大多数型号。需要较大的PM 20灰尘通量来匹配观察约束,显示出大气负荷的粗尘。我们获得粉尘排放,垂直整合,粉尘气溶胶光学深度,(表面)浓度和湿润和干燥沉积通量的网格数据集,其被季节和粒度分解。随着我们的结果表明,该数据集比当前模型模拟和Merra-2粉尘再分析产品更准确,可用于改善地球系统对粉尘影响的量化。

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