Apparent Susceptibility Contrast Distribution of Continental Lithosphere in China and Its Surroundings: Implications to Regional Tectonics

Abstract:

Lithospheric magnetic field characterizes response of magnetic properties of rocks, which are mainly dependent on mineral and temperature variations. Hence, lithospheric magnetic structure brings important information to understand tectonic and thermal processes in the crust and uppermost mantle. In particular, the reliable global geomagnetic field models with large-scales based on satellite magnetic measurements provide regional view of the lithospheric magnetic structure. Here, with smallest and flattest constraints we use the inversion method based on the single layer model to calculate the spatial distribution of apparent susceptibility of continental lithosphere in China and its surroundings. It should be noted that: (1) magnetic anomaly data we used has removed the effect of global oceanic remanent magnetization, (2) the error of magnetic anomaly data is estimated from statistical analysis among MF7, GRIMM_L120, CHAOS5 and CM5 models, (3) the magnetic layer is bounded by the bottom of sediment and the Moho from CRUST1.0 model and is discretized into ellipsoidal prisms with equal angles in latitude and longitude, and (4) an adaptive subdivision & Gauss-Legendre quadrature with fixed order is adopted to solve the forward problem and IGRF11 is utilized as inducing field model. Since the missing longest wavelength components in the lithospheric magnetic field models and the so-called magnetic annihilators, the Apparent Susceptibility Contrast (ASC) distribution is obtained. The ASC distribution has obvious variations and illustrates the mosaic continent with old blocks, orogenic belts, rework fragments and also earthquake regions/zones. Moreover, the ASC distribution provides new insights and evidences of the destruction of North China Craton and geodynamic processes of Tibetan plateau and Baikal rift etc. This study is supported by China Postdoctoral Science Foundation (Grant No.: 2015M572217) and Natural Science Fund of Hubei Province (Grant No.: 2015CFB361).