## 4 Discussion
An inspection of Figures 5 and 6 reveals that this is also true for global seismicity. Especially for the six strongest EQs of \(M\geq 8.5\) during our 46 years study period, Figure 5 reveals that for \(R=\)200 km \(\langle\)EPS\(\rangle\) at the lattice points closest to their epicenters takes values from 7% to 50%. Only 4% of the lattice points examined lie in this range of EPS values, showing that \(\langle\)EPS\(\rangle\) maps for \(R=\)200 km certainly provide information about the epicenter of a future strong EQ. This is also strengthened by the fact that even when we consider the case of Figure 6, which involves smaller in magnitude EQs (but also strong with \(M\in[7.7,8.3]\)) the corresponding \(\langle\)EPS\(\rangle\) closest to the epicenters vary from 7% to 77%, which correspond to just 5% of the points of the \(1^{\circ}\times 1^{\circ}\) lattice on which we made the calculation. We have to mention that in Figure 6g,h, we also included the \(\langle\)EPS\(\rangle\) maps estimated on the dates of \(\beta_{160,min}\), although such minima do not satisfy the Conditions (10) and (11) to be considered as 'precursory' fluctuation mimina. This was made in order to show that the methodology of Reference [79], where we just considered local variability minima for drawing \(\langle\)EPS\(\rangle\) maps, can also be applied in the global scale. In summary, we can say that the combination of earthquake nowcasting with the study of the variability minima of the order parameter of seismicity not only reveals useful information for the epicenters of the EQs that followed the 'precursory' fluctuation minima identified in Reference [13], i.e., those inserted in the first nine rows in Table 2, but may also highlight the epicenters of the most recent five strongest EQs in the globe during the almost seven year period from 1 January 2015 to 31 January 2022. As already mentioned, in Reference [13], the Conditions (10) and (11) have been established for identifying 'precursory' fluctuation minima in the global scale by means of NTA. Opening a prediction window of nine months on the date of appearance of \(\beta_{160,min}\), this initial study has led to six true positive results (hits) preceding the strongest \(M\geq 8.5\) EQs in the GCMT catalog. When such a strong EQ occurs, the alarm window terminates. The study of Reference [13] also produced three false alarms leading to the corresponding three nine-month windows, which do not include any \(M\geq 8.5\) EQ in the last but one panel of Figure 4. These false alarms are related to the order parameter fluctuation minima that preceded the Papua-Indonesia, Solomon Islands, and Iquique-Chile EQs;  
Figure 8: The mean value \(\overline{\langle\)EPS\(\rangle}\) (red circles) over all the grid points of the average EPS maps for the six \(M\geq 8.5\) EQs (see Table 2 and Figure 5) versus the coarse grain radius \(R\). It exhibits a power law behavior and the corresponding power law fit is shown in blue. see the newly constructed \(\langle\)EPS\(\rangle\) maps in Figure 6a-c, respectively. Apart from providing this epicentral information, the present work also extends that study for the period from 1 October 2014 to 31 January 2022. The present study led to the alarms shown by the brown binary (0/1)--or dichotomous (ON/OFF)--line in Figure 4. A careful inspection of this Figure reveals that three more false alarms appear, see the last three rows in Table 1. Interestingly, these three new false alarms could be correlated with the two strongest EQs of \(M=8.3\) that took place since 1 October 2014, while the third would be related with the Alaska \(M=7.8\) EQ [123] that took place on 22 July 2020, the stress changes of which triggered [124] the 2021 \(M=8.2\) Chignik EQ [125]. Thus, one may support the view that these false alarms are at least related with the strongest EQs during the last seven years, none of which, however, had magnitude \(M\geq 8.5\). At this point, we need to incorporate the results of [PERSON] et al.