A downscaling and bias correction method for climate model ensemble simulations of local-scale hourly precipitation.

Ensemble simulations of climate models are used to assess the impact of climate change on precipitation, and require downscaling at the local scale. Statistical downscaling methods have been used to estimate daily and monthly precipitation from observed and simulated data. Downscaling of short-term precipitation data is necessary for more accurate prediction of extreme precipitation events and related disasters at the regional level. In this study, we developed and investigated the performance of a downscaling method for climate model simulations of hourly precipitation. Our method was designed to recognize time-varying precipitation systems that can be represented at the same resolution as the numerical model. Downscaling improved the estimation of the spatial distribution of hourly precipitation frequency, monthly average, and 99th percentile values. The climate change in precipitation amount and frequency were shown in almost all areas by using the 50 ensemble averages of estimated precipitation, although the natural variability was too large to compare with observations. The changes in precipitation were consistent with simulations. Therefore, our downscaling method improved the evaluation of the climatic characteristics of extreme precipitation events and more comprehensively represented the influence of local factors, such as topography, which have been difficult to evaluate using previous methods.

Dispersion characteristics of radioactive materials estimated by wind patterns.

The radioactive materials are generally concentrated downwind of their origins when the prevailing winds blow continuously in one direction. If this principle determined the pattern of dispersion in all cases, dispersion directions could be estimated by wind patterns. However, this hypothesis has not been sufficiently verified because of the complexity of dispersion processes and weather systems. Here, we show that dispersion directions, which are divided into four ranges, can be estimated by wind patterns using a machine learning approach. The five-year average hit rates of the directions of dispersion estimated using near-surface winds exceed 0.85 in all months. The dispersion directions can be estimated up to 33 hours in advance using forecast winds. In particular, high hit rates exceeding 0.95 are achieved in January and March, when large-scale weather systems dominate. These results indicate that the dispersion directions are determined by the wind patterns that correspond to large-scale weather systems and diurnal circulation patterns in most cases. Our findings also provide more reliable information on dispersion patterns with reduced uncertainties, given that reasonable skill is achieved at a sufficient lead time for evacuation.

Estimation of Dietary Intake of Radionuclides and Effectiveness of Regulation after the Fukushima Accident and in Virtual Nuclear Power Plant Accident Scenarios.

Evaluation of radiation exposure from diet is necessary under the assumption of a virtual accident as a part of emergency preparedness. Here, we developed a model with complete consideration of the regional food trade using deposition data simulated by a transport model, and estimated the dietary intake of radionuclides and the effectiveness of regulation (e.g., restrictions on the distribution of foods) after the Fukushima accident and in virtual accident scenarios. We also evaluated the dilution factors (i.e., ratios of contaminated foods to consumed foods) and cost-effectiveness of regulation as basic information for setting regulatory values. The doses estimated under actual emission conditions were generally consistent with those observed in food-duplicate and market-basket surveys within a factor of three. Regulation of restricted food distribution resulted in reductions in the doses of 54⁻65% in the nearest large city to the nuclear power plant. The dilution factors under actual emission conditions were 4.4% for radioiodine and 2.7% for radiocesium, which are ~20 times lower than those used in the Japanese provisional regulation values after the Fukushima accident. Strict regulation worsened the cost-effectiveness for both radionuclides. This study highlights the significance and utility of the developed model for a risk analysis of emergency preparedness and regulation.

Long-distance transport of radioactive plume by nocturnal local winds.

Radioactive plumes can spread far and wide depending on wind conditions. The plumes often frequently reached the Tokyo metropolitan area, which is approximately 200 km away from the Fukushima Daiichi nuclear power plant, under spatially heterogeneous wind fields in March 2011. To reduce exposure to radioactive plumes, the behaviour of the plumes must be known. However, the transport mechanism of radioactive plumes is not fully understood. Using a regional climate model, we show that multiple diurnal cycle processes play a key role in the frequent transport of radioactive plumes to the Tokyo metropolitan area. The observed data and hindcast results indicate that the radioactive plume moves along the local winds, which comprise the northeasterly local wind (NELW) associated with the meso-scale low-pressure system (meso-low) and the northerly sea wind (NSW) during the night. The long-term analysis and sensitivity simulations also show the nocturnal processes that the NELW caused by the meso-low and the NSW are formed east of the Tokyo metropolitan area and from Fukushima offshore east of the Tokyo metropolitan area, respectively, when neither winter monsoons nor extra-tropical cyclones are predominant. These findings indicate that the radioactive plumes could reach faraway places frequently via nocturnal local processes.