4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Data Selection Model Parameterization Results: Statistics, Lithospheric Field, Core Field Perspective

4th Swarm QWG Meeting 2 – 5 December 2014 GFZ Potsdam/D

• Data Selection• Model Parameterization• Results: Statistics, Lithospheric Field, Core Field• Perspective …


• 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 < 2o

• scalar data from polar regions if Em < 0.8 mV/m

• “Gradient” (horizontal difference) data:• only scalar, no vector gradient• Inclusion of periods of higher geomagnetic activity (Kp < 3o, |d RC/dt | < 3

nT/hrand of dayside non-equatorial (> ±10 QD latitude) data

Data Selection


Data Distribution


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


Model Residual Statistics


Crustal Field


Normalized coefficient difference


Crustal Field Map

SIFM – MF7Backus-effect signaturein high degree (n > 60) terms

Br at surface, n = 16 - 65


Secular Variation


Secular Variation Map

Br at Core Mantle Boundary, n = 1 - 11


Scalar residuals vs. latitude


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


Inter-satellite calibration of SW-CHow to calibrate VFM(C) without ASM(C) ?Mapping of F : SW-A SW-C

• FASM(A)

• subtract Fmodel(A), add Fmodel(C) …

• … to obtain an estimate of F’ (C)• use this value to calibrate VFM(C)

all data: s = 0.55 nTnightside non polar: s = 0.28 nT

Comparison FASM (A C) – FASM (C)

daysidenightside


SIFM without ASM(C)

Inter-satellite calibration of VFM(C) using ASM(A)

SIFM-type model from FVFM(C), without ASM(C)

Documents

4 th Swarm QWG Meeting 2 – 5 December 2014GFZ Potsdam/D Data Selection Model Parameterization Results: Statistics, Lithospheric Field, Core Field Perspective