Earth, Planets and Space (Mar 2023)
Prediction of volcanic ash concentrations in ash clouds from explosive eruptions based on an atmospheric transport model and the Japanese meteorological satellite Himawari-8: a case study for the Kirishima-Shinmoedake eruption on April 4th 2018
Abstract
Abstract Prediction of ash concentrations in volcanic ash clouds for the Kirishima-Shinmoedake eruption on April 4th, 2018 is performed on the basis of an atmospheric transport model and the Japanese meteorological satellite Himawari-8. The retrieval algorithm for Himawari-8 (referred to as the “Optimal Volcanic Ash Algorithm”, OVAA) provides two-dimensional properties of volcanic ash clouds, such as cloud heights and total column mass loading, whereas it does not provide ash cloud thickness which is required to make an initial condition for the atmospheric transport model. To estimate ash cloud thickness immediately after an eruption, here, a wind shear index is introduced. The wind shear index includes an empirical constant parameter $$T_c$$ T c ; a small value of $$T_c$$ T c leads to thick ash clouds, whereas a large value of $$T_c$$ T c leads to thin ash clouds. In this study, the value of $$T_c$$ T c is optimized empirically in the following two ways: (1) a comparison between the total column mass loadings in the prediction and that in the OVAA estimation and (2) a comparison between the estimated ash cloud thickness and the observed ash cloud thickness by lidar measurements. These two comparisons suggest the optimal value of $$T_c$$ T c is 0.5 $$-$$ - 0.6, and then, the uncertainty of the ash clouds thickness estimation to be $$\sim$$ ∼ 700 m. In an operation, this estimation of $$T_c$$ T c can be used as a fixed value to estimate the ash cloud thickness for a future eruption. In this case, the ash concentration predictions can be obtained immediately after the OVAA estimation. The ash concentrations prediction for $$T_c$$ T c =0.6 provides areas of high contamination (>4 mg/m $$^3$$ 3 ) and low contamination (<2 mg/m $$^3$$ 3 ). This classification of ash concentration in ash clouds has been required by the aviation industry, and is helpful information to assess safe areas and routes for airline operations. Graphical Abstract
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