The impact of surface wind data assimilation on the predictability of near-surface plume advection in the case of the fukushima nuclear accident

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Abstract

We investigated the predictability of plume advection in the lower troposphere and the impact of AMeDAS surface wind data assimilation by using radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. We conducted two experiments of radioactive plume predictions over eastern Japan for March 15, 2011 with a 3-km horizontal resolution using the Japan Meteorological Agency non-hydrostatic weather forecast model and local ensemble transform Kalman filter (JMANHM-LETKF) data assimilation system. The assimilated meteorological data were obtained from the standard archives collected for the Japan Meteorological Agency operational numerical weather prediction and the AMeDAS surface wind observations. The standard archives do not contain land-surface wind observations. The modeled radioactive cesium concentrations were examined for plume arrival times at 40 observatories. The mean error of the plume arrival times for the standard experiment (assimilating only the standard archives) was 82.0 min with a 13-h lead-time on an average. In contrast, the mean error of the AMeDAS experiment (assimilating both the standard archives and AMeDAS surface wind observations) was 72.8 min, which was 9.2 min (11 %) better than that of the standard experiment. This result indicates that the plume prediction has a reasonable accuracy for the environmental emergency response and the prediction can be significantly improved by the surface wind data assimilation.

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Sekiyama, T. T., Kajino, M., & Kunii, M. (2017). The impact of surface wind data assimilation on the predictability of near-surface plume advection in the case of the fukushima nuclear accident. Journal of the Meteorological Society of Japan. Meteorological Society of Japan. https://doi.org/10.2151/jmsj.2017-025

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