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Tides Of Man — Descent. Know something about this song or lyrics? Add it to our wiki. Read More Edit Wiki. Descent song meanings. Add your thoughts 2 Comments. General Comment It gives me the chills every time I listen to this song.

Some sort of higher being. I haven't really sat down long enough long enough to really pull apart each section, but by far, favourite song off of empire theory album. The correlation coefficient and phase difference in hours lag were calculated using cross correlations in order to obtain the largest correlation between SL and wind data. The negative and positive correlation coefficients represent an inverse and direct relationship, respectively, with values close to -1 and 1 representing the highest correlation.

Values near zero do not demonstrate an existent relationship.

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The harmonic analysis performed for the SL data is based on the Fast Fourier Transform, which uses tidal harmonic components for the calculation of amplitudes and phases of tidal harmonic constants, providing the importance of each constituent. The results were obtained through the computer program called T-tide, following the methodology developed by Pawlowicz et al.

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From the results obtained in the harmonic analysis, the Form number F was calculated by dividing the sum of the diurnals O1 and K1 by the semidiurnal constants M2 and S2. Thus, the relative importance of diurnal and semidiurnal constituents is determined and it is possible to classify the tidal regime in a given region by following the classification proposed by Defant , apud Miranda The mean tidal range MTR resulted from the average of all high SL plus the average of all low SL observed over tidal and subtidal time series.

The maximum high and low SL represents the major and minor amplitudes reached by the water level, respectively. SL values above and below two standard deviations STD were selected for each mooring, and then the maximum and minimum SL events were separated from the rest.

In order to obtain a seasonal scenario, the number of positive and negative SL events for each season was quantified. Occurrences of values above and below three STDs were also selected, which may be related to extreme events.

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The MTR for all tide time series was 0. The average for all subtidal oscillations in the low-frequency time series was 0. The difference between the maximum and minimum level in the raw time series was 2. However, when the high- frequency oscillations tides were removed, a maximum variation of 1.

Nonetheless, when the oscillations caused by tides were analyzed alone, a maximum difference of 0. On August 12, , the lowest SL was recorded among all the time series, 1. This event was greatly accompanied by the media, being called "the super retreat" of the sea. The SL remained below the mean level for approximately hours, reaching its maximum after 54h of the beginning. This phenomenon was related to a strong meteorological system, an anticyclone on the Atlantic Ocean, that caused intense and persistent southwards winds on the entire SBCS.

It notes that this event occurred at spring tide period. Table 2 presents in detail the values of tidal and subtidal averages for each mooring and the values of the maximum SL at each frequency above and below zero or mean SL.

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It is important to notice that SL can reach 1. Figures 2a , 3a , 4a and 5a show the raw SL time series for each mooring. Figures 2b , 3b , 4b and 5b red color present the SL filtered data, i. It is possible to notice that in most seasons Figure 2 , Figure 3 between September and February, and the beginning of Figure 5 the tidal and subtidal oscillations are proportional in amplitude. However, in Figure 4 and at the end of Figure 5 , the magnitude of the amplitude of subtidal oscillations is greater than tidal oscillations.

These periods coincide with the winter and autumn seasons in the Southern Hemisphere. Table 3 shows the duration in days sum of duration in hours of SL events above and below two STDs for the raw data series by season. The total number of these positive and negative peaks of SL events and the number of events that exceeded three STDs are also displayed. It is worth mentioning that these extreme events three STDs only occurred during spring tides. Table 4 shows in detail the tidal and subtidal variances and the alongshore wind variance at high and low frequencies.

The spectral analysis of all SL raw data and the alongshore wind Figures 6a and 6b shows a great amount of energy at low frequencies, which corresponds to periods between 20 and 8 days 0. It is also possible to observe that the largest amount of energy in the SL variability occurred in the autumn green and winter blue. These results demonstrate a greater variability of SL and wind speed time series at low frequencies, which also shows a clear relationship between wind and SL variations.

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It is also possible to observe in Figure 6a a great amount of energy at high frequencies that are associated with diurnal 25h and semidiurnal 12h tides, especially during the summer months black. Sea level left and alongshore wind right. The cross correlation between the alongshore wind and SL for each season resulted in a coefficient between 0.

This corroborates with the results found in the spectral analysis, in which the alongshore wind is the main driving mechanism for local SL. The cross correlation between cross-shore wind and SL resulted in a coefficient between 0. The Form number calculated for each season resulted in values between 1.

One exception occurred in autumn , in which the F number was equal to 1. A possible explanation for this result could be the difference observed between the K1 and S2 amplitudes, since the largest and the smallest amplitudes of K1 and S2, respectively, were measured during this period, which consequently increases the resulting F number.

Corroborating with the visual inspection of tidal and subtidal time series Figures 2 , 3 , 4 and 5 , statistical analyses Table 4 and Figure 6 indicated that, in some seasons, around almost half of the energy involved in SL oscillations could be attributed to tidal oscillations. These results demonstrated that, even though the averages of astronomical tide amplitudes are considered small by the literature and also by the findings of this paper 0.

Thus, not only the variance of tidal oscillations but also the mean amplitude led us to the conclusion that the astronomical tide cannot be totally neglected in oceanographic studies in the RS coast. Usually in the literature Rocha et al. This reason led many studies to disregard the astronomical tides in their analyses. Few research works in the study area have broken this paradigm created by that misinterpretation of data results. Soares et al. One of the main conclusions was that regional circulation depends on a combination of tides, winds and river plumes.

Spectral analysis of SL and alongshore wind shows that the most part of the energy is found at low frequencies with coincident peaks, demonstrating a clear relationship between wind and SL variations. This can be interpreted as an indication that the wind is an important driving mechanism for local SL oscillations in time scales from hours to days. Another important aspect is the large differences among the SL time series with clear seasonal patterns.

As shown, the wind has a large influence on the local SL variations, so the wind seasonal variability directly affects the SL variance. Cold fronts that invert the wind direction reach Southern Brazil more frequently between May and September austral autumn and winter. From October to April austral spring and summer , cold fronts are less frequent in this region as they present a more zonal and maritime displacement Escobar et al.

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This seasonal pattern in SL variability, showing a higher intensity of positive extreme events during autumn and winter, has already been observed in a region further north from the study area, also associated with atmospheric frontal systems Campos et al. The results from the cross correlation between the alongshore wind and SL for each season demonstrated the effect of the wind on the SL oscillations. This corroborates with the findings from the spectral analysis, in which the alongshore wind is the main driving mechanism for the local SL.

The positive coefficients from the correlations can be explained by the Ekman balance model Ekman, for the Southern Hemisphere, where southward alongshore winds induce a decrease in the water level upwelling and northward alongshore winds cause an increase in it downwelling. The cross correlation between cross-shore winds and SL resulted in small coefficients, which is an indication of their poor relationship.

The Ekman transport in the RS coast had already been observed but in association with the water circulation Andrade et al.


A larger number of positive maximum events greater than two STDs occurred during the winter and autumn, with exception of autumn , when fewer events were observed. However, this can be partially explained by the high STD of this time series the largest of all. Negative peaks showed a uniform pattern of occurrence between seasons. Extreme atmospheric events such as the passage of intense extra-tropical cyclones happen more frequently in the winter and autumn months Machado and Calliari, ; Saraiva et al. It is important to note that the peaks reached only by the subtidal frequency are much lower than the peaks as a whole.