22 research outputs found

    Stochastic Inversion of P-to-S Converted Waves for Mantle Composition and Thermal Structure: Methodology and Application

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    We present a new methodology for inverting P‐to‐S receiver function (RF) waveforms directly for mantle temperature and composition. This is achieved by interfacing the geophysical inversion with self‐consistent mineral phase equilibria calculations from which rock mineralogy and its elastic properties are predicted as a function of pressure, temperature, and bulk composition. This approach anchors temperatures, composition, seismic properties, and discontinuities that are in mineral physics data, while permitting the simultaneous use of geophysical inverse methods to optimize models of seismic properties to match RF waveforms. Resultant estimates of transition zone (TZ) topography and volumetric seismic velocities are independent of tomographic models usually required for correcting for upper mantle structure. We considered two end‐member compositional models: the equilibrated equilibrium assemblage (EA) and the disequilibrated mechanical mixture (MM) models. Thermal variations were found to influence arrival times of computed RF waveforms, whereas compositional variations affected amplitudes of waves converted at the TZ discontinuities. The robustness of the inversion strategy was tested by performing a set of synthetic inversions in which crustal structure was assumed both fixed and variable. These tests indicate that unaccounted‐for crustal structure strongly affects the retrieval of mantle properties, calling for a two‐step strategy presented herein to simultaneously recover both crustal and mantle parameters. As a proof of concept, the methodology is applied to data from two stations located in the Siberian and East European continental platforms.This work was supported by a grant from the Swiss National Science Foundation (SNF project 200021_159907). B. T. was funded by a DĂ©lĂ©gation CNRS and CongĂ© pour Recherches et Conversion ThĂ©matique from the UniversitĂ© de Lyon to visit the Research School of Earth Sciences (RSES), The Australian National University (ANU). B. T. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 79382

    International Geomagnetic Reference Field: the thirteenth generation

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    In December 2019, the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group (V-MOD) adopted the thirteenth generation of the International Geomagnetic Reference Field (IGRF). This IGRF updates the previous generation with a definitive main field model for epoch 2015.0, a main field model for epoch 2020.0, and a predictive linear secular variation for 2020.0 to 2025.0. This letter provides the equations defining the IGRF, the spherical harmonic coefficients for this thirteenth generation model, maps of magnetic declination, inclination and total field intensity for the epoch 2020.0, and maps of their predicted rate of change for the 2020.0 to 2025.0 time period

    Implementation of a digital timing recovery circuit for CDMA applications

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    May 2002), the NPOESS Cross-track Infrared Sounder (CrIS), the MetOp Infrared Atmospheric Sounding Interferometer

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    Errors due to wireless transmission can have an arbitrarily large impact on a compressed file. A single bit error appearing in the compressed file can propagate during a decompression procedure and destroy the entire granule. Such a loss is unacceptable since this data is critical for a range of applications, including weather prediction and emergency response planning. The impact of a bit error in the compressed granule is very sensitive to the error’s location in the file. There is a natural hierarchy of compressed data in terms of impact on the final retrieval products. For the considered compression scheme, errors in some parts of the data yield no noticeable degradation in the final products. We formulate a priority scheme for the compressed data and present an error correction approach based on minimizing impact on the retrieval products. Forward error correction codes (e.g., turbo, LDPC) allow the tradeoff between error correction strength and file inflation (bandwidth expansion). We propose segmenting the compressed data based on its priority and applying different-strength FEC codes to different segments. In this paper we demonstrate that this approach can achieve negligible product degradation while maintaining an overall 3-to-1 compression ratio on the final file. We apply this to AIRS sounder data to demonstrate viability for the sounder on the next-generation GOES-R platform
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