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This research is devoted to the determination of hidden dependencies between the flow of particles that come from the Sun and precipitation-induced floods in the United Kingdom (UK). The analysis covers 20 flood events during the period from October 2001 to December 2019. The parameters of solar activity were used as model input data, while precipitations data in the period 10 days before and during each flood event were used as model output. The time lag of 0–9 days was taken into account in the research. Correlation analysis was conducted to determine the degree of randomness for the time series of input and output parameters. For establishing a potential causative link, machine learning classification predictive modeling was applied. Two approaches, the decision tree, and the random forest were used. We analyzed the accuracy of classification models forecast from 0 to 9 days in advance. It was found that the most important factors for flood forecasting are proton density with a time lag of 9, differential proton flux in the range of 310–580 keV, and ion temperature. Research in this paper has shown that the decision tree model is more accurate and adequate in predicting the appearance of precipitation-induced floods up to 9 days ahead with an accuracy of 91%. The results of this study confirmed that by increasing technical capabilities, using improved machine learning techniques and large data sets, it is possible to improve the understanding of the physical link between the solar wind and tropospheric weather and help improve severe weather forecasting.

In Finland, in the period 1996–2017, 28,434 forest fires were recorded (an average of 1,292.5 per year), and the total burned area was 11,922 ha (an average of 541.9 ha per year). In both cases, a statistically non-significant downward trend was recorded. Forest fires in Finland do not represent a particularly significant problem, primarily due to climatic characteristics, well-organized fire protection, and low density of population. The research of climate influence included the Atlantic Multidecadal Oscillation (AMO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO). The statistically significant values (p ≤ .05) of Pearson correlation coefficient were recorded for the August values of NAO and the surface area of burned forest (−0.44), the June values of NAO and the average surface area of forest burned per fire (−0.51) and the May AO values and the average surface area of forest burned per fire (−0.45). For the June values of NAO and the average surface area of forest burned per fire, the Lomb periodogram shows four significant peaks, and the match is at two, at 2.4 and 3.4 years, which supports the hypothesis of the connection between NAO and forest fires in Finland.

The data on forest fires in Portugal in the period 1980–2015 were used in the research: the annual number of forest fires, the annual burned area and the average burned area per fire. Increasing trend of the annual number of forest fires (statistically significant at p≤0.01), non-significant increasing trend of the annual burned area and decreasing trend of the average burned area per fire (statistically significant at p≤0.01) were recorded. Portugal is the most endangered country by forest fires in comparison with the other European countries. During the research period, fires in Portugal covered 23.6% of the total burned area in five the most affected European countries (Portugal, Spain, France, Italy and Greece). In the research of the connection between forest fires and the Atlantic Multidecadal Oscillation (AMO) Pearson correlation coefficient (R) was used. Monthly, seasonal and annual values of the AMO index were used in calculations. All R values recorded for the annual number of fires were positive and statistically significant at p≤0.01. The highest values were recorded for August (0.543) and for summer (0.525). With the annual burned area all R values were also positive and the highest one on the seasonal level was for summer (0.359). With the average burned area per fire all R values were negative (−0.428 was recorded for winter). The results of the research could be applied in the fire danger forecast for periods of several months. Other climate indices should also be considered in future research.

In Finland, in the period 1996–2017, 28,434 forest fires were recorded (an average of 1,292.5 per year), and the total burned area was 11,922 ha (an average of 541.9 ha per year). In both cases, a statistically non-significant downward trend was recorded. Forest fires in Finland do not represent a particularly significant problem, primarily due to climatic characteristics, well-organized fire protection, and low density of population. The research of climate influence included the Atlantic Multidecadal Oscillation (AMO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO). The statistically significant values (p ≤ .05) of Pearson correlation coefficient were recorded for the August values of NAO and the surface area of burned forest (−0.44), the June values of NAO and the average surface area of forest burned per fire (−0.51) and the May AO values and the average surface area of forest burned per fire (−0.45). For the June values of NAO and the average surface area of forest burned per fire, the Lomb periodogram shows four significant peaks, and the match is at two, at 2.4 and 3.4 years, which supports the hypothesis of the connection between NAO and forest fires in Finland.

Climatic indices complexly display the climate of a place, and certainly influence its more qualitative characterization. In this paper, the specificity of the climate is analyzed, such as the degree of continentality and aridity, in the example of the city of Podgorica. The climate was considered on the basis of the data for almost the entire instrument period (1951–2017). The results obtained for thermal continentality show that maritime influences are primary and predominant, but the influence of the continent is also significant. In a hygric sense, the climate of Podgorica is characterized as poorly arid to poorly humid with significant oscillations during the year. The warmer period of the year, especially the summer, has the characteristics of arid climate. The colder period of the year, especially from November to February, has the characteristics of humid and even perhumidic climate, while the transitional seasons show signs of semi-aridity and semi-humidity.

The data on the water temperature of the Sava in Serbia (hydrological stations Šabac and Belgrade, period 1961–2015) were used for the research, as well as the data on the surface air temperature. The temperature trends were determined and the significance (at p≤0.05 and p≤0.01) was established on the basis of the t-test. The Pearson correlation coefficient (R) was used for the calculation of the correlation. Increasing trends of the water temperature of the Sava were recorded in all cases at both stations. However, in the case of the HS Šabac, the trends for 6 months (February–April and September–November) were not statistically significant. In the case of the HS Belgrade, all the calculations (except for April) showed statistically significant increasing trends, which can be explained by anthropogenic influence. High level of correlation between the surface air temperature and the water temperature was also determined. In this research, the lowest values of R were recorded for October (0.561 for Belgrade), and on the seasonal level, for autumn (0.625 for Šabac). The research on the correlation between the water temperature of the Sava River and the NAO index showed the highest values of R for January (0.512 for HS Šabac and 0.528 for HS Belgrade). On the seasonal level, the highest values were recorded for winter (0.422 for HS Šabac and 0.432 for HS Belgrade).

Forest fires in Portugal (June 17–24, 2017) destroyed 64 lives and caused considerable material damage. The coronal hole CH807 and the energy region S5710 were in the geoeffective position on the Sun immediately before the outbreak of fires. In the period that preceded it, as well as at the time of the fires, increased values of the solar wind (SW) parameters (temperature, speed and density of particles) were recorded. In addition, a geomagnetic disorder was recorded. The shape and size of the burning areas, as well as the low air pressure over Portugal indicate the possibility of the effect of positively charged particles that came from the area south, i.e. southwest of Portugal. Nevertheless, it is a specific case that would have to be investigated in more detail.

The study examines the connection between the Atlantic Multidecadal Oscillation (AMO) and the forest fires (the annual number of fires, the annual burned area and the average burned area per fire) in France in the period 1980–2014. In order to determine the strength of the correlation connection Pearson correlation coefficient (R) was used. Monthly, seasonal and annual values of AMO were used in calculations, and one year phase shift was performed (the values for the previous year were used). In burned area the highest values of R on the monthly level were recorded for April (-0.474) and January (-0.470), and on the seasonal level for winter (-0.459) and spring (-0.447). These values are statistically significant at the level of p≤0.01. By phase shifting the highest level of correlation was obtained for the autumn (-0.489). In the average burned area per fire on a monthly level the highest value of R was for January (-0.522), and on seasonal for winter (-0.506). By phase shifting the highest value of R was obtained for autumn (-0.522). In the number of fires the highest values were recorded by phase shifting for September (-0.382) and autumn (-0.337). All R values recorded during the study had a negative sign (the correlation is antiphase). In addition, downward trends were determined for all three examined indicators of forest fires in the researched period (1980–2014). Results of the research could be used as a basis for the long-term forecast of the risk of forest fires, and the approach used in the research could be applied for the other areas of the world. However, the more detailed research of the effects of other teleconnections are necessary.