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Published byChad Cain Modified over 9 years ago
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Data Selection Model Parameterization Results: Statistics, Lithospheric Field, Core Field Perspective …
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Vector and scalar data: selection criteria similar to CHAOS-4 nightside data (sun at least 10 below horizon) |d RC/dt | < 2 nT/hr vector data (in instrument frame) from non-polar regions (< 55 QD latitude) if Kp < 2 o scalar data from polar regions if E m < 0.8 mV/m “Gradient” (horizontal difference) data: only scalar, no vector gradient Inclusion of periods of higher geomagnetic activity (Kp ±10 QD latitude) data Data Selection
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Data Distribution
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Static (crustal) field up to degree n = 70 Linear time dependence (secular variation) for n = 1 – 13 Large-scale magnetospheric field (similar to CHAOS-4 parameterization) Co-estimation of instrument alignment parameters (Euler angles) in bins of 10 days Model Parameterization
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Model Residual Statistics
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Crustal Field
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Normalized coefficient difference
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Crustal Field Map SIFM – MF7 Backus-effect signature in high degree (n > 60) terms B r at surface, n = 16 - 65
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Secular Variation
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Secular Variation Map B r at Core Mantle Boundary, n = 1 - 11
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Scalar residuals vs. latitude
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Conclusions Inclusion of gradient data improves crustal field and secular variation Use of data during higher magnetic activity and from dayside (14% 46% of all data) crustal field mainly improved by EW gradient data secular variation mainly improved by NS gradient data Scalar difference SW-A – SW-C: Mean: -120 pT rms: 280 pT
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Inter-satellite calibration of SW-C How to calibrate VFM(C) without ASM(C) ? Mapping of F : SW-A SW-C F ASM (A) subtract F model (A), add F model (C) … … to obtain an estimate of F’ (C) use this value to calibrate VFM(C) all data: = 0.55 nT nightside non polar: = 0.28 nT Comparison F ASM (A C) – F ASM (C) dayside nightside
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4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D SIFM without ASM(C) Inter-satellite calibration of VFM(C) using ASM(A) SIFM-type model from F VFM (C), without ASM(C)
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