ABSTRACT: Cloudiness is an important climate parameter, and it is closely related to insolation, temperature, and precipitation. Total cloud cover (TCC) data along with the number of cloudless (CL) and overcast (OC) days from 18 stations in Montenegro during the period 1961-2017 were used to determine the seasonal trends and possible causes of cloudiness variability. The Mann-Kendall test and Sen’s slope were used for trend detection. We found statistically significant (p < 0.05 and p < 0.10) decreasing (increasing) trends in TCC (the number of CL days) in winter, spring and summer. The exception was in autumn, when an increase (decrease) in the TCC (CL days) was shown, but in most cases, these changes were insignificant. The number of OC days declined in coastal and central regions, while a positive trend was found in the northern region for all seasons. The increase in the number of CL days during the summer and winter was more pronounced compared to the decreasing trend in the number of OC days. Pearson’s correlation (r) was used to access the relationship between cloudiness and principal modes of atmospheric variability such as North Atlantic Oscillation (NAO), Summer North Atlantic Oscillation (SNAO), Arctic Oscillation (AO), East Atlantic Oscillation (EA), East Atlantic-West Russian Oscillation (EAWR), Scandinavian Pattern (SCAND), Polar-Eurasian Oscillation (POLEUR), North Sea-Caspian Pattern (NCP), and South Oscillation (SOI) as well as regional patterns of climate variability—the Mediterranean Oscillation (MOI) and Western Mediterranean Oscillation (WeMO). A significant consistency (r > 0.60, p < 0.05) was found between time series of certain atmospheric circulation patterns and cloud parameters (NAO, AO, EAWR, SCAND, NCP, and MOI-1), especially in the colder half of the year.

中文翻译：

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1961-2017年期间黑山多云变化的趋势和可能原因

摘要：多云是重要的气候参数，它与日照，温度和降水密切相关。利用黑山的总云量（TCC）数据以及1961-2017年期间黑山18个站点的无云（CL）和阴天（OC）天数，来确定季节性趋势和云量变化的可能原因。使用Mann-Kendall检验和Sen斜率进行趋势检测。我们发现，冬季，春季和夏季，TCC（CL天数）的减少（增加）趋势具有统计学意义（p <0.05和p <0.10）。例外是秋天，当TCC（CL天）显示增加（减少）时，但在大多数情况下，这些变化并不明显。沿海和中部地区的OC天数减少，而北部地区所有季节都呈积极趋势。与OC天数减少的趋势相比，夏季和冬季CL天数的增加更为明显。皮尔逊相关系数（r）用于了解云量与大气变化的主要模式之间的关系，例如北大西洋涛动（NAO），夏季北大西洋涛动（SNAO），北极涛动（AO），东大西洋涛动（EA），东部大西洋西俄涛动（EAWR），斯堪的纳维亚模式（SCAND），极欧亚涛动（POLEUR），北海里海涛动（NCP）和南涛动（SOI）以及气候变化的区域性模式-地中海涛动（MOI）和西地中海涛动（WeMO）。显着一致性（r> 0.60，p <0。