Orographic effects on the transport and deposition of volcanic ash: A case study of Mount Sakurajima, Japan

Abstract

Volcanic ash is a major atmospheric hazard that has a significant impact on local populations and international aviation. The topography surrounding a volcano affects the transport and deposition of volcanic ash, but these effects have not been studied in depth. Here we investigate orographic impacts on ash transport and deposition in the context of the Sakurajima volcano in Japan, using the chemistry‐resolving version of the Weather Research and Forecasting model. Sakurajima is an ideal location for such a study because of the surrounding mountainous topography, frequent eruptions, and comprehensive observing network. At Sakurajima, numerical experiments reveal that across the 2–8ϕ grain size range, the deposition of “medium‐sized” ash (3–5ϕ) is most readily affected by orographic flows. The direct effects of resolving fine‐scale orographic phenomena are counteracting: mountain‐induced atmospheric gravity waves can keep ash afloat, while enhanced downslope winds in the lee of mountains (up to 50% stronger) can force the ash downward. Gravity waves and downslope winds were seen to have an effect along the dispersal path, in the vicinity of both the volcano and other mountains. Depending on the atmospheric conditions, resolving these orographic effects means that ash can be transported higher than the initial injection height (especially for ash finer than 2ϕ), shortly after the eruption (within 20 min) and close to the vent (within the first 10 km), effectively modifying the input plume height used in an ash dispersal model—an effect that should be taken into account when initializing simulations.

The Effect of Wind and Atmospheric Stability on the Morphology of Volcanic Plumes From Vulcanian Eruptions

“…The specific values for the parameters ( c 1 =3.8×10 −5 , c 2 =2.6, c 3 =−1.3×10 5 ) were chosen using monthly ashfall data gathered by the Kagoshima prefectural government at 62 locations between 2009 and 2013 so that the Pearson product‐moment correlation coefficient is maximized. The method was seen to provide accurate estimates for the total erupted mass for individual eruptions (∼10% error) that have been successfully used in specific eruption case studies (Poulidis et al, , ). In the rest of the paper this method will be referred to as I2016.…”

“…This could be explained due to the uncertainties of the data involved—predominately U , U 0 , and the TGSD. The wind field is known to change due to the effect of topography (e.g., Poulidis et al, ) as well as due to the time difference between the eruption and the sounding. In the calculations here U 0 was based on FPLUME output but the exit velocity at the vent was arbitrarily set at 120 m/s.…”

Current Challenges in Orographic Flow Dynamics: Turbulent Exchange Due to Low-Level Gravity-Wave Processes

“…Existing parametrisations do not account for the larger-scale foehn flow or represent the turbulent mixing of heat, moisture and constituents. The impacts of this omission are likely to be profound, for example with implications for weather forecasts in and downwind of mountainous regions; for hazard mitigation with respect to wild fires [30], clear air turbulence for aviation [12] and volcanic ash dispersion [2]; for modelling chemical transport and air quality [31]; and for long term predictions of ice sheet mass balance and stability [32].…”

“…This is particularly problematic for regional numerical weather prediction (NWP) in complex terrain, for air-quality modelling in mountainous regions, and for global Earth System Models, which require the representation of complex processes such as atmospheric chemistry and aerosols among others. The application of models to forecast impacts such as avalanches, wild fires, or volcanic ash dispersion [2], also requires an improved treatment of the way orographic flows affect turbulent transport. In the case where atmospheric models are used to drive impact models, or where forecasts of hazardous turbulent gusts are required, diagnostics are needed which account for the sub-grid variability associated with these orographic processes.…”

Experimental High-Resolution Forecasting of Volcanic Ash Hazard at Sakurajima, Japan

“…As a part of the system, JMA uses a Lagrangian transport model to run scheduled forecasts of lapilli and ashfall in three hour blocks using forecast data, as well as emergency forecasts for eruptions with plume heights over 2.5 km agl [13]. However, even at the finer local forecast resolution used (horizontal grid spacing of 2 km), the forecasts are too coarse to fully resolve localized circulations and windplume interactions [24,25], which can in turn affect dispersal and deposition of volcanic ash [3,26,27].…”