eprintid: 1587 rev_number: 10 eprint_status: archive userid: 4 dir: disk0/00/00/15/87 datestamp: 2015-09-24 07:35:28 lastmod: 2018-03-28 09:47:29 status_changed: 2015-09-24 07:35:28 type: article metadata_visibility: show creators_name: Mignan, Arnaud creators_name: Woessner, Jochen creators_id: jochen.woessner@sed.ethz.ch corp_creators: Swiss Seismological Service, ETH Zurich corp_creators: Swiss Seismological Service, ETH Zurich title: Estimating the magnitude of completeness for earthquake catalogs subjects: MP2_2 divisions: EPOS-P full_text_status: none abstract: Assessing the magnitude of completeness Mc of instrumental earthquake catalogs is an essential and compulsory step for any seismicity analysis. Mc is defined as the lowest magnitude at which all the earthquakes in a space-time volume are detected. A correct estimate of Mc is crucial since a value too high leads to under-sampling, by discarding usable data, while a value too low leads to erroneous seismicity parameter values and thus to a biased analysis, by using incomplete data. In this article, we describe peer-reviewed techniques to estimate and map Mc. We provide examples with real and synthetic earthquake catalogs to illustrate features of the various methods and give the pros and cons of each method. With this article at hand, the reader will get an overview of approaches to assess Mc, understand why Mc evaluation is essential and an a non-trivial task, and hopefully be able to select the most appropriate Mc method to include in his seismicity studies. date: 2012-04-01 publication: Community Online Resource for Statistical Seismicity Analysis publisher: Community Online Resource for Statistical Seismicity Analysis pagerange: 1-45 id_number: DOI: 10.5078/corssa-00180805 official_url: http://dx.doi.org/10.5078/corssa-00180805 access_IS-EPOS: limited software_references: Completeness_Magnitude_Estimation owner: Publisher citation: Mignan, Arnaud and Woessner, Jochen (2012) Estimating the magnitude of completeness for earthquake catalogs. Community Online Resource for Statistical Seismicity Analysis. pp. 1-45. DOI: https://doi.org/10.5078/corssa-00180805