## 3 Results and Discussion
### Analysis of the Rainfall Series  
Analysis of the daily rainfall data showed that the highest value of the historical series of Maringa (1980-2017) occurred on 1 November 2016 (Figure 4A). However, this event was only 7.26% greater than the occurrence verified on 19 June 2012 (157 mm). The occurrence of this event also has a spatial context, because although the daily rainfall was the most significant in the historical series of Maringa, this was not reported in other evaluated series. Therefore, although the record of 1 November 2016 was locally relevant, the daily rain on that date was not that expressive for the entire northern region of the state. A comparison equivalent to that can be seen in [18], for the Alto Alegre station (code 2251033, municipality of Colorado, PR) (Figure 4). Considering the same period evaluated in this work, the daily (Figure 4A) and monthly (Figure 4B) precipitation were not extraordinary, though the six months accumulate presents a RP higher than 100 years (Figure 4C).  
By analyzing the monthly values (Figure 4B), we observed that January 2016 was the third rainiest month in the historical series (419.8 mm), behind February 1997 (446 mm) and January 1990 (421.6 mm). Analyzing the historical series, in several other moments there were months with precipitation above 350 mm. Thus, the monthly values interpreted in isolation seem not to have been relevant during EN 15-16.  
Based on the series of monthly values, consecutive rainy periods were analyzed, so that for EN 15-16 the following sequence was observed: 236.7 mm in September 2015; 312.2 mm in October 2015; 369.6 mm in November 2015; 327 mm in December 2015; 419.8 mm in January 2016; 382.1 mm in February 2016. In these six months, the rainfall cumulate was 2049.4 mm. A statistic sum of the rainfall value of the current month plus the five previous months was generated (Figure 4C). Considering this sum, since 1980 there has been no similar event, with the second largest event occurring in 1983 (difference of 524.1 mm: \(-\)34.36%) and the third in 1997 (difference of 563.1 mm: \(-\)37.88%), both periods that were also under the influence of El Nino. The 2049.4 mm cumulate in February 2016 was so impressive that it presents a 4.43 standard deviation above the mean, based on the 1980-2017 period.  
When analyzing historical series from other locations referred to in Table 1, similar patterns were observed, in which the isolated daily and monthly rainfall did not seem to show an extraordinary event, but when performing the sum of these six months, the series indicated peaks similar to that presented in Figure 4C. Thus, the sum of the rainfall for six months was taken as the variable representing the extraordinary rainfall arising from EN 15-16.  
Similarly with this study, the six-month cumulative rainfall was used by [19; 20; 21] as a climatic precursor for landslides in the southern Italian Apennines. These studies showed that the piezometric fluctuations and the landslide activity in the slope have a strong relation with the seasonal climate. In particular, the rainfall cumulated between 160 to 180 days is very related to deep and slow landslides (deeper than 3 m).  
Figure 3: Southern Oscillation Index (SOI) for the period from May 2013 to October 2017. The red line represents a seven-month moving average. The blue line indicates the period from September 2015 to February 2016. Data source: NOAA [10].