Atmospheric activity concentration of 7Be in the air was monitored during the period of one year from September 2015 to September 2016 at Ostrava, Czech Republic, with a two-day frequency that is shorter compared to a standard 7-day frequency of routine 7Be measurements. Simultaneously, relevant meteorological data (temperature, rainfall amount, precipitation particle size and speed, tropopause height, and PM10 concentrations) and the sunspot number were accumulated. Weighted linear regression analysis applied to the 7Be atmospheric activity concentration, the measured meteorological explanatory variables and the sunspot number revealed temperature as the most statistically significant explanatory variable. The tree model proved temperature as the most important explanatory variable and predicted the threshold value separating low and high temperature behavior of 7Be at about 13 °C (2-day average). A simple local two-layer (stratosphere and troposphere) atmospheric model was then applied to the data analysis. The model is able to fit the data for a larger accumulation period (6 days).

中文翻译：

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7Be大气活动浓度和气象数据：统计分析和两层大气模型。

在2015年9月至2016年9月的一年中，对捷克共和国俄斯特拉发的大气中7Be的大气浓度进行了监测，其两天频率比常规7Be测量的标准7天频率短。同时，收集了相关的气象数据（温度，降水量，降水粒度和速度，对流层顶高度和PM10浓度）和黑子数。对7Be大气活动浓度进行加权线性回归分析，测得的气象解释变量和黑子数表明温度是统计上最有意义的解释变量。该树模型证明温度是最重要的解释变量，并预测了在约13°C（2天平均值）下分离7Be的低温和高温行为的阈值。然后将一个简单的本地两层（平流层和对流层）大气模型应用于数据分析。该模型能够在更长的累积期间（6天）内拟合数据。