Earthquake Magnitude Conversion Problem

A unified moment magnitude earthquake catalog for Northeast India

“…When both the magnitude types contain measurement errors and the use of the standard least-squares regression procedure leads to systemic errors as high as 0.3-0.4 (Castellaro et al 2006) in magnitude conversion, it is inadequate and, even more important, it may result in catalog incompleteness. General orthogonal regression (GOR) analysis is more appropriate to estimate regression relationships between different magnitude types (Thingbaijam et al 2008;Ristau 2009;Das et al 2012aDas et al , 2012bDas et al , 2013Das et al , 2014aDas et al , 2014bDas et al , 2018aDas et al , 2018b. However, it is well addressed in different studies on GOR procedure usability to obtain an unbiased estimate of the dependent variable (Das et al 2012a(Das et al , 2012b(Das et al , 2013(Das et al , 2014a(Das et al , 2014b(Das et al , 2018a(Das et al , 2018bWason et al 2012).…”

“…Errors of different magnitude scales are shown in Table 1. In this study, an improved GOR methodology was used, as suggested by Das et al (2018b), for deriving regression relationships to change body and surface wave magnitudes into moment magnitudes on a regional and global basis. A dataset of 9845 earthquake events was used in terms of M w in the magnitude range 1.6-8.7 belonging to the region studied (lat.…”

GIS-Based Mapping of Seismic Parameters for the Pyrenees

“…To work with a homogeneous catalog, all the events must possess the same kind of magnitude, and the preferred scale has been M w for the advantages mentioned earlier. Different authors have proposed global and regional parameters to convert the original size into M w [35][36][37][71][72][73][74]. Given that both independent and dependent variables have errors, a reduced major axis (RMA) is currently preferred to a least-square ordinary regression [36,71].…”

“…Different authors have proposed global and regional parameters to convert the original size into M w [35][36][37][71][72][73][74]. Given that both independent and dependent variables have errors, a reduced major axis (RMA) is currently preferred to a least-square ordinary regression [36,71]. In this work, the conversion from the original size of every event to M w has been conducted from the parameters suggested by Cabañas et al [36], as they are specific for the Iberian Peninsula and adjacent areas.…”

“…Assuming self-similarity, M c is simply the magnitude increment at which the FMD departs from the linear trend in the log-lin plot [75]. The estimate of M c can be assessed from Figure 5 that both independent and dependent variables have errors, a reduced major axis (RMA) is currently preferred to a least-square ordinary regression [36,71]. In this work, the conversion from the original size of every event to Mw has been conducted from the parameters suggested by Cabañas et al [36], as they are specific for the Iberian Peninsula and adjacent areas.…”