TY - JOUR A1 - Platz, Anna A1 - Weckmann, Ute T1 - An automated new pre-selection tool for noisy Magnetotelluric data using the Mahalanobis distance and magnetic field constraints JF - Geophysical journal international N2 - In Magnetotellurics (MT) natural electromagnetic field variations are recorded to study the electrical conductivity structure of the subsurface. Thereby long time-series of electromagnetic data are subdivided into smaller segments, which are Fourier transformed and typically averaged in a statistically robust manner to obtain MT transfer functions. Unfortunately, nowadays the presence of man-made electromagnetic noise sources often deteriorates a significant fraction of the recorded time-series by overprinting the desired natural field variations. Available approaches to obtain undisturbed and high quality MT results include, for example robust statistics, remote reference or multi-station analyses which aim at the removal of outliers or uncorrelated noise. However, we have observed that intermittent noise often affects a certain time span resulting in a second cluster of transfer functions in addition to the expected true MT distribution. In this paper, we present a novel criterion for the detection and pre-selection of EM noise in form of outliers or additional clusters based on a distance measure of each data segment with regard to the centre of the data distribution. For this purpose, we utilize the Mahalanobis distance (MD) which computes the distance between two multivariate points considering the covariance matrix of the data that quantifies the shape and the size of multivariate data distributions. As the MD considers the covariance matrix, it corrects not only for different variances but also for any correlation between the data. The computation of both, the mean value and covariance matrix, is susceptible to ouliers (e.g. noise) and requires a statistically robust estimation. We tested several robust estimators, for example median absolute deviation or minimum covariance determinant algorithm and finally implemented an automatic criterion using a deterministic minimum covariance determinant algorithm. We will present results using MT data from various field experiments all over the world, which illustrate successfull data improvement. This approach is able to remove scattered data points as well as to reject complete data cluster originating from noise sources. However, like all purely statistical algorithms the criterion is limited to cases where the majority of the recorded data is well-behaved, that is noise content is below 50 per cent. If the majority of data points originates from noise sources, the new criterion will fail if used in an automatic way. In these cases, additional input by the user either manually or in an automated fashion can be utilized. We therefore suggest to use an add-on criterion to back the MD selection and subsequent robust stacking in form of a physically motivated constraint based on the magnetic incidence direction. This property indicates whether the magnetic field originates from various sources in the far field or from a strong and well defined source in the near field. KW - Magnetotellurics KW - Statistical methods KW - Time-series analysis Y1 - 2019 U6 - https://doi.org/10.1093/gji/ggz197 SN - 0956-540X SN - 1365-246X VL - 218 IS - 3 SP - 1853 EP - 1872 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Trauth, Martin H. A1 - Asrat, Asfawossen A1 - Düsing, Walter A1 - Foerster, Verena A1 - Krämer, K. Hauke A1 - Marwan, Norbert A1 - Maslin, Mark A. A1 - Schäbitz, Frank T1 - Classifying past climate change in the Chew Bahir basin, southern Ethiopia, using recurrence quantification analysis JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - The Chew Bahir Drilling Project (CBDP) aims to test possible linkages between climate and evolution in Africa through the analysis of sediment cores that have recorded environmental changes in the Chew Bahir basin. In this statistical project we consider the Chew Bahir palaeolake to be a dynamical system consisting of interactions between its different components, such as the waterbody, the sediment beneath lake, and the organisms living within and around the lake. Recurrence is a common feature of such dynamical systems, with recurring patterns in the state of the system reflecting typical influences. Identifying and defining these influences contributes significantly to our understanding of the dynamics of the system. Different recurring changes in precipitation, evaporation, and wind speed in the Chew Bahir basin could result in similar (but not identical) conditions in the lake (e.g., depth and area of the lake, alkalinity and salinity of the lake water, species assemblages in the water body, and diagenesis in the sediments). Recurrence plots (RPs) are graphic displays of such recurring states within a system. Measures of complexity were subsequently introduced to complement the visual inspection of recurrence plots, and provide quantitative descriptions for use in recurrence quantification analysis (RQA). We present and discuss herein results from an RQA on the environmental record from six short (< 17 m) sediment cores collected during the CBDP, spanning the last 45 kyrs. The different types of variability and transitions in these records were classified to improve our understanding of the response of the biosphere to climate change, and especially the response of humans in the area. KW - Paleoclimate dynamics KW - Eastern Africa KW - Pleistocene KW - Holocene KW - Time-series analysis KW - Recurrence plot Y1 - 2019 U6 - https://doi.org/10.1007/s00382-019-04641-3 SN - 0930-7575 SN - 1432-0894 VL - 53 IS - 5-6 SP - 2557 EP - 2572 PB - Springer CY - New York ER -