Horizontal Resolution Dependence of Atmospheric Simulations of the Fukushima Nuclear Accident Using 15-km, 3-km, and 500-m Grid Models

Abstract

We investigated the horizontal resolution dependence of atmospheric radionuclide (Cs-137) simulations of the Fukushima nuclear accident on March 15, 2011. We used Eulerian and Lagrangian transport models with low-(15-km), medium-(3-km), and high-(500-m) resolutions; both models were driven by the same meteorological analysis that was prepared by our data assimilation system (NHM-LETKF) for each horizontal resolution. This preparation was necessary for the resolution-dependent investigation, excluding any interpolation or averaging of meteorological fields. In the results, the 15-km grid analysis could not reproduce Fukushima's mountainous topography in detail, and consequently failed to depict a complex wind structure over mountains and valleys. In reality, the Cs-137 plume emitted from the Fukushima Daiichi Nuclear Power Plant (FDNPP) was mostly blocked by Mt. Azuma and other mountains along the Naka-dori valley after crossing over Abukuma Mountains on March 15, 2011. However, the 15-km grid simulations could not represent the blockage of the Cs-137 plume, which unnaturally spread through the Naka-dori valley. In contrast, the 3-km and 500-m grid simulations produced very similar Cs-137 concentrations and depositions, and successfully produced the plume blockage and deposition along the Naka-dori valley. In conclusion, low-resolution (15-km grid or greater) atmospheric models should be avoided for assessing the Fukushima nuclear accident when a regional analysis is needed. Meanwhile, it is reasonable to use 3-km grid models instead of 500-m grid models due to their similarities and the high computational burden of 500-m grid model simulations.

The Impact of Surface Wind Data Assimilation on the Predictability of Near-Surface Plume Advection in the Case of the Fukushima Nuclear Accident

“…For example, the JMA operational meso-GPV dataset was used by all regional models that participated in the multimodel intercomparison of Fukushima nuclear pollution predictions (Science Council of Japan (SCJ) 2014) except for two models. One was our model (Sekiyama et al 2015), which used an original meteorological dataset. The other model used the European Centre for Medium-Range Weather Forecasts (ECMWF) operational global GPV dataset.…”

“…The other model used the European Centre for Medium-Range Weather Forecasts (ECMWF) operational global GPV dataset. All models except Sekiyama et al (2015) utilized the GPV datasets that were prepared by others (i.e., JMA or ECMWF). However, for the purpose of our investigation, the GPV datasets have to be prepared by our own data assimilation system because we need to arrange a comparison of meteorological analyses performed in the presence or absence of surface wind data assimilation.…”

“…However, for the purpose of our investigation, the GPV datasets have to be prepared by our own data assimilation system because we need to arrange a comparison of meteorological analyses performed in the presence or absence of surface wind data assimilation. Hence, we utilized the meteorological data assimilation system of Sekiyama et al (2015) in this study to prepare the GPV datasets with and without land-surface wind data assimilation.…”

“…The meteorological data assimilation system of Sekiyama et al (2015) was developed by Kunii (2014) and is composed of the JMA's non-hydrostatic regional weather prediction model (JMANHM, cf., Saito et al 2006Saito et al , 2007 and the local ensemble transform Kalman filter (LETKF, cf., Miyoshi and Aranami 2006). In this study, this system was driven by 20 ensemble members and a 3-km horizontal resolution within the model domain of eastern Japan (215 × 259 grids, cf., Fig.…”

“…In this study, this system was driven by 20 ensemble members and a 3-km horizontal resolution within the model domain of eastern Japan (215 × 259 grids, cf., Fig. 2b of Sekiyama et al 2015). The covariance localization parameters were set to 50 km in the horizontal, 0.1 natural-logarithm-pressure coordinate in the vertical, and 3 hours in the time dimension for all observations.…”