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Dispersion characteristics of radioactive materials estimated by wind patterns

机译:通过风型估算放射性物质的扩散特性

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摘要

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.
机译:当盛行的风向一个方向连续吹动时,放射性物质通常集中在其起源的顺风处。如果该原理确定了所有情况下的散射模式,则可以通过风模式来估计散射方向。然而,由于分散过程和天气系统的复杂性,这一假设尚未得到充分验证。在这里,我们表明可以使用机器学习方法通​​过风模式来估计分为四个范围的散布方向。使用近地表风估计的分散方向的五年平均命中率在所有月份中均超过0.85。借助预报风,可以提前33个小时估算散射方向。特别是在大型天气系统占主导地位的一月和三月,实现了超过0.95的高命中率。这些结果表明,在大多数情况下,弥散方向是由与大型天气系统和日循环模式相对应的风型确定的。我们的发现还为分散模式的不确定性降低提供了更可靠的信息,前提是在足够的疏散准备时间达到了合理的技能。

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