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Review and uncertainty assessment of size-resolved scavenging coefficient formulations for below-cloud snow scavenging of atmospheric aerosols

机译:大气气溶胶云雾下扫雪的尺寸分辨扫气系数公式的回顾和不确定性评估

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Theoretical parameterizations for the size-resolved scavenging coefficient for atmospheric aerosol particles scavenged by snow (Λsnow) need assumptions regarding (i) snow particle-aerosol particle collection efficiency E, (ii) snow-particle size distribution N(Dp), (iii) snow-particle terminal velocity VD, and (iv) snow-particle cross-sectional area A. Existing formulas for these parameters are reviewed in the present study, and uncertainties in Λsnow caused by various combinations of these parameters are assessed. Different formulations of E can cause uncertainties in Λsnow of more than one order of magnitude for all aerosol sizes for typical snowfall intensities. E is the largest source of uncertainty among all the input parameters, similar to rain scavenging of atmospheric aerosols (Λrain) as was found in a previous study by Wang et al. (2010). However, other parameters can also cause significant uncertainties in Λsnow, and the uncertainties from these parameters are much larger than for Λrain. Specifically, different N(Dp) formulations can cause one-order-of-magnitude uncertainties in Λsnow for all aerosol sizes, as is also the case for a combination of uncertainties from both VD and A. Assumptions about dominant snow-particle shape (and thus different VD and A) will cause an uncertainty of up to one order of magnitude in the calculated scavenging coefficient. In comparison, uncertainties in Λrain from N(Dp) are smaller than a factor of 5, and those from VD are smaller than a factor of 2. As expected, Λsnow estimated from empirical formulas generated from field measurements falls in the upper range of, or is higher than, the theoretically estimated values, which can be explained by additional processes/mechanisms that influence field-derived Λsnow but that are not considered in the theoretical Λsnow formulas. Predicted aerosol concentrations obtained by using upper range vs. lower range of Λsnow values (a difference of around two orders of magnitude in Λsnow) can differ by a factor of 2 for just a one-centimetre snowfall (liquid water equivalent of approximately 1 mm). Based on the median and upper range of theoretically generated Λsnow and Λsnow values, it is likely that, for typical rain and snow events, the removal of atmospheric aerosol particles by snow is more effective than removal by rain for equivalent precipitation amounts, although a firm conclusion requires much more evidence.
机译:对于被雪清除的大气气溶胶颗粒(“雪”)的尺寸分辨清除系数的理论参数化需要以下假设:(i)雪颗粒-气溶胶颗粒收集效率 E ,(ii)雪颗粒尺寸分布< i> N(D p),(iii)雪粒终速度 V D ,以及(iv)雪粒横截面积 A 。在本研究中,对这些参数的现有公式进行了回顾,并评估了由这些参数的各种组合引起的Λnow的不确定性。对于典型的降雪强度,对于所有气溶胶尺寸, E 的不同配方都可能导致snow的不确定性超过一个数量级。在所有输入参数中, E 是不确定性的最大来源,类似于Wang等人先前的研究发现的对大气气溶胶(Λrain)的降雨清除。 (2010)。但是,其他参数也可能导致Λsnow的明显不确定性,并且这些参数的不确定性要比Λrain的不确定性大得多。具体来说,对于所有气溶胶尺寸,不同的 N(D )公式都可能导致Λsnow的一阶数量级不确定性,这两个 V < / i> D 和 A 。关于主要雪粒形状的假设(因此,不同的 V D 和 A )将导致最大不确定度达一个数量级。计算的清除系数。相比之下,来自 N(D p)的RAIN的不确定性小于5因子,来自 V D 的Λrain的不确定性小于a。因子2。正如预期的那样,根据现场测量产生的经验公式估算的Λsnow处于理论估计值的上限或高于理论估计的值,这可以用影响现场衍生的Λsnow的其他过程/机制来解释,但是在理论“雪”公式中未考虑。对于一厘米的降雪(液态水当量约为1毫米),通过使用较高范围的雪域值和较低范围的雪域值(雪域中的两个数量级的差异)可获得的预测气溶胶浓度可以相差2倍。 。根据理论生成的Λsnow和Λsnow值的中位数和上限,对于典型的降雨和降雪事件,对于相当的降水量,用雪清除大气气溶胶颗粒可能要比用降雨清除更有效,尽管结论需要更多的证据。

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