The 2019 Raikoke volcanic eruption - Part 1: Dispersion model simulations and satellite retrievals of volcanic sulfur dioxide
The 2019 Raikoke volcanic eruption - Part 1: Dispersion model simulations and satellite retrievals of volcanic sulfur dioxide
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DOI：
10.5194/acp-21-10851-2021
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发表时间：
2021-07-19
影响因子：
6.3
通讯作者：
Kristiansen, Nina, I
中科院分区：
文献类型：
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作者：
de Leeuw, Johannes;Schmidt, Anja;Kristiansen, Nina, I
火山喷发可能对社会造成重大破坏，而数值模型对于预测喷发物质的扩散至关重要。在这里，我们评估英国气象局数值大气扩散模拟环境(NAME)在模拟2019年6月21日至22日莱科克火山(北纬48.3度，东经153.2度)喷发时二氧化硫(SO2)云扩散的技能和局限性。这次喷发释放出约1.5+/-0.2 Tg的SO2，这是自2011年纳布罗喷发以来向平流层排放最大的SO2火山。我们模拟了北半球火山SO2云的时间演化，并将我们的模式模拟与对流层监测仪(Tropomi)和红外大气探测干涉仪(IASI)卫星SO2产品的高分辨率SO2测量进行了比较。我们发现，NAME准确地模拟了喷发后2-3周内观测到的SO2云的位置和水平范围，但在其标准配置下，无法捕捉到观测到的火山云中最高震级垂直柱密度(VCD)区域的范围和精确位置。用结构-幅度-位置(SAL)和分数技能(FSS)作为模型技能的度量，NAME显示了模拟喷发后12-17d云的水平范围的技能，其中SO2的VCD(以Dobson单位为单位，DU)在1DU以上。对于SO2云中主要被观测为小尺度特征的20DU以上的SO2VCDs，该模式仅显示出2-4d量级的技巧。这些高SO2-VCD区域的技术水平较低，部分原因是与Tropomi反演相比，模型模拟的SO2云在名称上过于分散。将NAME中使用的标准水平扩散参数减少4倍会导致在模拟的前5天中模型技能略有增加，但在更长的时间尺度上，与Tropomi测量相比，模拟的SO2云仍然过于扩散。NAME模拟高SO2 VCD的技能和NH-平均SO2质量负荷的时间演变由排放到平流层低层的SO2质量分数主导，这对2019年莱科克喷发是不确定的。当向平流层下部(11-18公里)排放0.9-1.1Tg的SO2，向对流层上部(8-11公里)排放0.4-0.7Tg的SO2质量负荷时，NAME模拟显示SO2质量负荷的峰值与NH的Tropomi(1.4-1.6Tg的SO2)的峰值相似，平均SO2电子折叠时间为14-15d。我们的工作说明了高分辨率卫星反演和扩散模式之间的协同如何能够识别像NAME这样的扩散模式的潜在局限性，这最终将有助于改进火山SO2云的扩散模拟工作。
Volcanic eruptions can cause significant disruption to society, and numerical models are crucial for forecasting the dispersion of erupted material. Here we assess the skill and limitations of the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) in simulating the dispersion of the sulfur dioxide (SO2) cloud from the 21-22 June 2019 eruption of the Raikoke volcano (48.3 degrees N, 153.2 degrees E). The eruption emitted around 1.5 +/- 0.2 Tg of SO2, which represents the largest volcanic emission of SO2 into the stratosphere since the 2011 Nabro eruption. We simulate the temporal evolution of the volcanic SO2 cloud across the Northern Hemisphere (NH) and compare our model simulations to high-resolution SO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) satellite SO2 products.We show that NAME accurately simulates the observed location and horizontal extent of the SO2 cloud during the first 2-3 weeks after the eruption but is unable, in its standard configuration, to capture the extent and precise location of the highest magnitude vertical column density (VCD) regions within the observed volcanic cloud. Using the structure-amplitude-location (SAL) score and the fractional skill score (FSS) as metrics for model skill, NAME shows skill in simulating the horizontal extent of the cloud for 12-17 d after the eruption where VCDs of SO2 (in Dobson units, DU) are above 1 DU. For SO2 VCDs above 20 DU, which are predominantly observed as small-scale features within the SO2 cloud, the model shows skill on the order of 2-4 d only. The lower skill for these high-SO2-VCD regions is partly explained by the model-simulated SO2 cloud in NAME being too diffuse compared to TROPOMI retrievals. Reducing the standard horizontal diffusion parameters used in NAME by a factor of 4 results in a slightly increased model skill during the first 5 d of the simulation, but on longer timescales the simulated SO2 cloud remains too diffuse when compared to TROPOMI measurements.The skill of NAME to simulate high SO2 VCDs and the temporal evolution of the NH-mean SO2 mass burden is dominated by the fraction of SO2 mass emitted into the lower stratosphere, which is uncertain for the 2019 Raikoke eruption. When emitting 0.9-1.1 Tg of SO2 into the lower stratosphere (11-18 km) and 0.4-0.7 Tg into the upper troposphere (8-11 km), the NAME simulations show a similar peak in SO2 mass burden to that derived from TROPOMI (1.4-1.6 Tg of SO2) with an average SO2 e-folding time of 14-15 d in the NH.Our work illustrates how the synergy between highresolution satellite retrievals and dispersion models can identify potential limitations of dispersion models like NAME, which will ultimately help to improve dispersion modelling efforts of volcanic SO2 clouds.