zmap a tool for analyses of seismicity patterns typical applications ...

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chosen on the basis of the linearity of the observed curves. Once this selection has been performed, the routine attempts to fit the background to the foreground by assuming two possibilities: (1) The background is first adjusted to fit the foreground by assuming a simple magnitude shift. The shift is estimated from the separation between the two curves and by using the minimum magnitude at which the curve departs from a linear fit by more than one standard deviation. (2) The background, Mback, is matched to the foreground, Mfore, by assuming a linear magnitude transformation (stretch or compression of magnitude scale) of the type (Zuniga and Wyss, 1995): Mfore = c * Mback + dM where c and dM are constants. Numerical results are given in a window which allow the possibility of interactively changing any of the shift, stretch or rate factor parameters (Figure 2.6). Results are also graphically displayed in a separate window which shows: a) The frequency-magnitude distribution of the foreground and the frequency-magnitude distribution of the corrected background, using the values for c and dM from the latest run. b) Non-cumulative histograms for both foreground and corrected background c) Magnitude signatures (if needed) Figure 2.6: Results of compare-fit. The values given include the best fit for two separate possibilities: a simple magnitude shift (ideally one would like to work with this value); and a magnitude stretch. In 18
this case, the routine found that a simple shift of +0.1 units applied to the background, would best fit the foreground, while if a stretch is chosen, one needs to apply a shift of +0.3 and a multiplicative factor of 0.82. Notice that in the selection panels, a simple magnitude shift of +0.1 is input, which resulted in the plot shown in Figure 2.7A. (B) (A) Figure 2.7. Comparison of rates as a function of magnitude for two time periods under the Compare-Fit option. The three panels correspond to the Frequency-Magnitude curves, normalized, the non-cumulative histogram as a function of magnitude, and the magnitude signatures for the original two periods (circles) and for the synthetic foreground as compared to the original background (crosses). (A) Results of applying a simple magnitude shift of +0.1 units, without any rate change. (B) Same as in (A) but including a rate change of 0.78 (equivalent to the -%22 change in percent given in Figure 2.5). The magnitude signature plot is useful for asserting the goodness of the fit from the latest run (bottom panel of Figures 2.7A and B). It shows the original magnitude signature, which results after comparing the two time periods, and a modeled signature obtained from comparing the synthetic foreground (i.e. the corrected background) to the original background. The best match between both signatures indicates that we have been able to model the observed behavior by applying the given corrections to the background. In the example, we can see that the shape of the signature is correctly modeled by applying a simple magnitude shift (Figure 2.7A) while a rate decrease is still necessary to model the position of the signature (Figure 2.7B). The Compare-fit option is also useful in case one needs to determine the relation between two different magnitude estimations for the same period and area. For this case, you would need to first concatenate the two data sets (“Combine two catalogs” option in the “Catalogs” pulldown menu from the Seismicity Map window) and treat them as separate time periods. 19
Page 1 and 2: ZMAP A TOOL FOR ANALYSES OF SEISMIC
Page 3 and 4: INTRODUCTION This cookbook is aimed
Page 5 and 6: Figure 2: Seismicity map of the ent
Page 7 and 8: Save new mat-file: At this point it
Page 9 and 10: Narrowing the target of investigati
Page 11 and 12: Figure 11: Resolution map with the
Page 13 and 14: Articles in which tools discussed i
Page 15 and 16: Figure 2.2: Genas1 window. The cumu
Page 17: Figure 2.5: Comparison of the rates
Page 21 and 22: cumulative number curve for M>1. ev
Page 23 and 24: Second: One may want to know the am
Page 25 and 26: Figure 3. 5: Z-menu window. Choosin
Page 27 and 28: each node and calculates for every
Page 30 and 31: Again the grid is chosen by using t
Page 33 and 34: Articles in which tools discussed i
Page 35 and 36: Figure 4.2: b-value maps of souther
Page 37 and 38: Figure 4.5: (a) Magnitude of comple
Page 39 and 40: Changes of b-values as a function o
Page 41 and 42: CHAPTER V Stress Tensor Inversions
Page 43 and 44: Inverting for the best fitting stre
Page 45 and 46: of S1 as a bar, and color codes the
Page 47 and 48: Using Gephart’s code An alternati
Page 49 and 50: #define VARIANCE_30 30 change to: #
Page 51 and 52: depicts the misfit value f. Please
Page 53 and 54: Lu, Z., M. Wyss, and H. Pulpan, Det
Page 55 and 56: • First rename mydata into a: a =
Page 57 and 58: CHAPTER VII Tips an tricks for maki
Page 59 and 60: Now lets change the axes setup. Sel
Page 61 and 62: Alternatively, you can print from t
Page 63: Working with interpolated color map

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