Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017https://doi.org/10.5194/gi-6-361-2017© Author(s) 2017. This work is distributed underthe Creative Commons Attribution 3.0 License.

In situ vector calibration of magnetic observatoriesAlexandre Gonsette, Jean Rasson, and François HumbledCentre de Physique du Globe, Royal Meteorological Institute, 5670 Dourbes, Belgium

Correspondence to: Alexandre Gonsette (agonsett@meteo.be)

Received: 3 March 2017 – Discussion started: 27 March 2017Revised: 29 June 2017 – Accepted: 13 July 2017 – Published: 25 September 2017

Abstract. The goal of magnetic observatories is to measureand provide a vector magnetic field in a geodetic coordi-nate system. For that purpose, instrument set-up and cali-bration are crucial. In particular, the scale factor and ori-entation of a vector magnetometer may affect the magneticfield measurement. Here, we highlight the baseline conceptand demonstrate that it is essential for data quality control.We show how the baselines can highlight a possible calibra-tion error. We also provide a calibration method based onhigh-frequency “absolute measurements”. This method de-termines a transformation matrix for correcting variometerdata suffering from scale factor and orientation errors. Wefinally present a practical case where recovered data havebeen successfully compared to those coming from a refer-ence magnetometer.

1 Introduction

Most magnetic observatories are built according to a stan-dardized or universally adopted scheme (Jankowski andSucksdorff, 1996) including at least a set of three major in-struments: a variometer, an absolute scalar magnetometer,and a declination and inclination flux instrument (DI-flux in-strument). The different data streams are combined to build aunique vector of magnetic field data. The variometer is a vec-tor magnetometer, which records variations of the magneticfield components at a regular interval (e.g. at 1 Hz). How-ever, this is not an absolute instrument. In particular, refer-ence directions, the vertical and geographical north, are notavailable. They usually work as near-zero sensors, so that anoffset must be added to the relative value of each compo-nent in order to adjust it and therefore determine the com-plete vector. Those offsets or baselines should be as constantas possible but may drift more or less depending on the en-

vironment stability and device quality. For instance, thermalvariations may affect the pillar stability. A baseline can alsosuffer from sudden variation due to an instrumental effect af-ter a (unwanted) motion like a shock due to maintenance staffor a change in the surrounding environment (Fig. 1). A reg-ular determination of the baselines is thus necessary to taketheir change into account. This is the main goal of the well-known “absolute measurements” that are carried out by thetwo other instruments.

First, a scalar magnetometer records the intensity of thefield |B|. Most of the time, a proton precession or an Over-hauser magnetometer is used for this task. Overhauser mag-netometer exploits the fact that protons perform precessionat a frequency proportional to the magnetic field accordingto

ωprecession = γ ‖B‖, (1)

where γ , the gyromagnetic ratio, is a fundamental physicalconstant (Mohr et al., 2016). Therefore, this magnetometercan be considered an absolute instrument.

The last instrument serves to determine the magnetic fieldorientation according to reference direction. Magnetic dec-lination is the angle between true north and the magneticfield in a horizontal plane, and the inclination is the anglebetween the horizontal plane and the field. In a conventionalobservatory, a DI-flux instrument (non-magnetic theodolite-embedding single-axis magnetic sensor) is manipulated byan observer according to a particular procedure (Kerridge,1988) taking about 15 min per measurement. This instrumentis also considered absolute because angles are measured ac-cording to geodetic reference directions. Due to this man-power dependency, the frequency of absolute measurementsdoes not exceed once per day (St Louis, 2012). However,new automatic devices such as AutoDIF (automatic DI-fluxinstrument; Gonsette et al., 2012) close the loop by automa-

Published by Copernicus Publications on behalf of the European Geosciences Union.

362 A. Gonsette et al.: In situ vector calibration of magnetic observatories

0 50 100 150 200 250 300 350Day of year 2013

-0.34

-0.32

-0.3

-0.28

-0.26

-0.24

-0.22

D0

[°]

Dourbes D0 baseline 2013

AutoDIFManual Zeiss 010B

Figure 1. Baseline example computed from conventional manualmeasurements (dark blue) and the automatic system (light blue). Inmid-2013, a baseline jump corresponding to an instrumental effectoccurred, proving that regular absolute measurement are crucial.

tising the DI-flux measurements procedure. Moreover, Au-toDIF is able to increase the frequency of baseline determi-nation by performing several measurements per day.

After collecting synchronised data from the three instru-ments, baselines are computed by using the relation for theCartesian coordinate system:

X0 (t)Y0 (t)Z0 (t)

= X(t)Y (t)Z (t)

− δX(t)δY (t)δZ (t)

, (2)where X(t), Y (t) and Z(t) are, at the time t , the tree con-ventional components of the field, pointing to the geographicnorth, eastward and downward respectively. The “0” indexrefers to the baseline spot measurements, while δ refers to thevariometer data. The full baseline measurement protocol in-cluding a set of four absolute declinations and four absoluteinclinations (even if only two are required for determiningall the unknowns) can be found in the literature; this can alsobe found for spherical and cylindrical configurations (Ras-son, 2005). The need for eight (at least six) measurementsis justified by the DI-flux sensor offset and misalignment. Abaseline function is then applied on these measurements us-ing various methods such as a least-squares polynomial orspline approximation. Finally, the vector field is constructedby adding the variometer values to the adopted baselines.

Equation (2) assumes a variometer properly set up with theZ axis vertical and theX axis pointing toward the geographicnorth. The scale factor of each component is also assumed tobe perfect.

A correct orientation is usually ensured by paying atten-tion during the set-up step, but its stability in time is not al-ways evident. Permafrost areas are examples of drifting re-gions (Eckstaller et al., 2007) where variometer orientationis not guaranteed. If the orthogonality errors are neglected,

the problem of calibration can be expressed as follows: XYZ

= Rz (γ )Ry(β)Rx (α) k1 0 00 k2 0

0 0 k3

δUδVδW

+

X0Y0Z0

, (3)where the Rx,y,z are an elementary rotation matrix and theki variables are the scale factors for each component. U ,V and W are the three variometers output into the sensorsreference frame. Calibration procedures can be divided intotwo categories. On one hand, the scalar calibration comparesscalar values computed from the vector magnetometer to ab-solute scalar values. This technique is exploited by satellitesbecause the vector reference field is not available. Never-theless, instruments are orbiting around the Earth (Olsen etal., 2003). The different scalar measurements from the scalarinstrument can therefore be compared to the scalar valuescomputed from the vector instrument. On the other hand, thevector calibration directly compares vector magnetometermeasurements to the reference vector value. Marusenkov etal. (2011) used a second variometer already calibrated as thereference. Previously, Jankowski and Sucksdorff (1996) pro-posed a comparison between the variometer data and the ab-solute measurements performed during disturbed days in or-der to calibrate the observatory. The development was madefor small angle errors (no more than 1–2◦), but Jankowskiand Sucksdorff (1996) suggested that the method could re-main valid for any angle. Jankowski and Sucksdorff (1996)also pointed out the difficulty in getting sufficiently strongmagnetic activity at low latitudes. The method presented inthis paper is relatively close to the latter, except for the factthat the automatic DI-flux instrument can generate a largenumber of absolute measurements within a short time (e.g.48 absolute measurements every 24 h), leading to a fast au-tomatic calibration process also at low latitude or during sig-nificantly magnetic periods.

The method presented in this document is related to a vari-ometer in XYZ configuration. However, other configurationsmay also be considered. For instance, many observatories setup their magnetometers in an HDZ configuration, whereH isthe direction of the magnetic north, D the declination and Zthe vertical component. Working directly with theD compo-nent would lead to non-linear equations. Nevertheless, mostmodern variometers are based on fluxgate sensor technology.Thus, the recorded signal is the orthogonal projection of thefield along the fluxgate sensitive axis. The residue (δE) ex-pressed in nT (nanotesla) can be used like any geographiccomponent and converted afterward into a declination valueaccording to

δD =180π

asin(δE

H

). (4)

Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017 www.geosci-instrum-method-data-syst.net/6/361/2017/

A. Gonsette et al.: In situ vector calibration of magnetic observatories 363

The same approach can be used for a DFI magnetometer.However, the reader should keep in mind that not all vari-ometer axes might have a compensating coil allowing themto work in the entire field. Indeed, recording the D and Ivariations is similar to a DI-flux process. The sensor is quasi-perpendicular to the field so that the residues are close tozero. The recorded signal could rapidly saturate.

2 Calibration error detection

Before solving the calibration problem, it could be useful togive some clues for detecting required adjustments. Indeed,it is difficult, when only examining definitive data, to detecta few nanotesla errors in daily amplitude. Direct comparisonwith other observatories requires them to be close enoughwhile many observatories cannot afford to buy an auxiliaryvariometer. Fortunately, baselines are useful tools for check-ing data. As described below, they are affected by calibrationerrors, and, if they are measured with a sufficiently high fre-quency, particular errors can be highlighted.

2.1 Scale factor error

Let us consider an observatory working with a variometer,such as a LEMI-025, in a Cartesian coordinate system. Eachsensor converts a real magnetic signal expressed in nanoteslainto a more suitable format (usually a voltage). This con-verted signal passes through an ADC providing, in turn, adigital representation of the initial signal. A scale factor isthen used to convert the true signal into a digitised signal.Consider the X component:

δXvoltage = k1 δXreal, (5)δXdigital = k2δXvoltage = k δXreal, (6)

where δXreal is the real magnetic variation in nT toward theXdirection, k1 is a scale factor in volt/nT converting the mag-netic field signal into an electrical signal, δXvoltage is the im-age of the field signal expressed in volts, k2 is a scale factorin nT/volt converting the electric signal into a digital value,k = k2k1 is the dimensionless scale factor converting the realmagnetic signal into its digital representation. k should be asclose to 1 as possible.

Supposing now a difference between the digital and realvariation of a component resulting from a badly calibratedscale factor, the baseline measurement will be affected bythis error:[

X∗0 (t)Y ∗0 (t)Z∗0 (t)

]=

[X(t)Y (t)Z (t)

]−

[kx 0 00 ky 00 0 kz

][δX(t)δY (t)δZ (t)

], (7)[

X∗0 (t)Y ∗0 (t)Z∗0 (t)

]=

[X0 (t)Y0 (t)Z0 (t)

]+

[(1− kX) 0 0

0 (1− kY ) 00 0 (1− kZ)

][δX(t)δY (t)δZ (t)

]. (8)

The (*) symbol denotes the erroneous baseline affected bya scale factor error. The baseline then varies with respect toits corresponding variometer component value, meaning thata correlation exists between both.

The scale factor is usually factory calibrated and should bestable over time. It is certainly true but there are many situ-ations for which the scale factor is not known exactly (e.g. ahomemade instrument) or differs from its factory value (e.g.a repair after a lightning strike may affect the instrument pa-rameters). The impact of a scale factor error also depends onthe magnitude of the magnetic activity. A 1 % error for theH component scale factor at mid-latitude would lead to nomore than 0.5 nT during quiet days. On the other hand, thesame percent error at high latitude during a stormy day mayaffect the data by several nT.

2.2 Orientation error

Now, let us consider once again the same XYZ variometerbut this time presenting an orientation error. That could bedue, for instance, to a levelling error caused by a bad set-up oran unstable basement and/or an X axis pointing to any otherdirection than the conventional one. The given componentsare affected by this orientation error and do not correspondto the expected ones. This is the reason why instruments suchas ASMO (Alldregde, 1960) or any other three-axis magne-tometers will never be considered as a full magnetic obser-vatory.

Rasson (2005) treated the simplified case of a rotation θaround the Z axis. The orthogonality between componentswas assumed to be perfect. In that particular case, the relativereal values at time t are given by[δX(t)δY (t)δZ (t)

]=

[cos(θ) −sin(θ) 0sin(θ) cos(θ) 0

0 0 1

][δU(t)δV (t)δW(t)

]. (9)

The X0 baseline, for instance, should be computed as

X0 =X(t)− cos (θ)δU(t)+ sin(θ)δV (t). (10)

If no correction is applied, the observed baseline gives thefollowing form:

X∗0 =X0− (1− cos(θ))δU(t)− sin(θ)δV (t). (11)

In this case, a correlation exists between the baseline andanother relative component. Figure 2 shows an example ofa variometer rotated around its vertical axis by 1.7◦. Thehigh-resolution baseline (blue) computed by means of an au-tomatic DI-flux instrument presents the same trend as theδY (red) component. The peak–peak amplitude is more than2 nT.

The general case is much more complex in particular ifthe orientation error is combined with a significant scale fac-tor error. Indeed, the term (1− cos(θ)) in Eq. (11) may beinterpreted either as a scale factor error or as an orientationerror.

www.geosci-instrum-method-data-syst.net/6/361/2017/ Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017

364 A. Gonsette et al.: In situ vector calibration of magnetic observatories

202 202.5 203 203.5 204 204.5 205 205.5 206

Day of year 2016

20 069

20 070

20 071

20 072

20 073

X0

[nT

]

Correlation between X0 baseline and /Y (Dourbes LEMI 025)

-100

-80

-60

-40

-20

0

20

40

60

/Y

[nT

]

Figure 2. Light blue: X0 baseline computed from high-frequencyabsolute measurements. Dark blue: variometer Y component fromthe LEMI-025. Because the variometer is not properly oriented, astrong correlation appears between X0 and Y.

3 Calibration process

Absolute measurements, before giving baselines, provide ab-solute or spot values of the magnetic field. When performedwith a sufficiently high frequency (e.g. once per hour), thegenerated magnetogram can be compared to the variometervalue. Therefore, a vector calibration can be done as if a ref-erence variometer was available.

A DI-flux instrument, either a manual system such as aZeiss 010-B or an automatic system like the AutoDIF, is af-fected by the sensor offset and misalignments errors. A singlespot measurement is therefore computed from a set of fourdeclination (index 1 to 4) and four inclination (index 5 to8) records. The eight synchronised variometer values as wellas the eight scalar measurements are averaged. Thus, eachspot value and corresponding variometer value is computedas follows:

Xm =

∑Fi

8cos

(I5+ I6+ I7+ I8

4

)cos

(D1+D2+D3+D4

4

), (12)

Ym =

∑Fi

8cos

(I5+ I6+ I7+ I8

4

)sin(D1+D2+D3+D4

4

), (13)

Zm =

∑Fi

8sin(I5+ I6+ I7+ I8

4

), (14) δUmδVm

δWm

= 18

∑δUi∑δVi∑δWi

, (15)where, the “i” index refers to the records 1 to 8 synchronisedwith the four declinations and the four inclinations.

Let us consider a series of n samples built from Eqs. (12)–(15). The general case, including orthogonality errors, can be

expressed by rewriting Eq. (3) as follows:[XmYmZm

]T=

[a b cd e fg h i

][δUmδV mδWm

]T+

[X0Y0Z0

], (16)

where Xm = [Xm1, . . .,Xmn]T , Y = [Ym1, . . .,Ymn]T , Z =[Zm1, . . .,Zmn]T are the time series of X, Y and Z spotvalues recorded by means of the absolute instruments andδU = [δUm1, . . ., δUmn]T , δV = [δVm1, . . ., δVmn]T , δW =[δWm1, . . ., δWmn]T are the three component time series ofthe variometer. Because the period of acquisition is relativelysmall (a few days is enough), the baseline values X0, Y0, Z0are assumed to be constant. For each component X, Y andZ, the problem consists of solving a linear system, where atime series of spot values and the quasi-synchronised threevariometer components are the input. Assuming the systemto be overdetermined, the latter is solved in the least-squaressense. Equation (17) gives the coefficients corresponding tothe X component (others are similar):

a

b

c

X0

= (ATA)−1ATX, (17)where A=

[δU δV δW 1

]. Once the whole coef-

ficients matrix is determined, the variometer data are re-dressed: δXδYδZ

T = a b cd e fg h i

δUδVδW

T . (18)Equation (18) refers to all variometer data and not only theaveraged data obtained from Eq. (15). For each set of abso-lute measurements, the three corrected baselines can be pro-cessed in a conventional way. Considering an XYZ variome-ter, the Z0 baseline is first computed and then X0 and Y0 arecomputed:

Z0 =F5+F6+F7+F8

4sin

(I5+ I6+ I7+ I8

4

)−δZ5+ δZ6+ δZ7+ δZ8

4, (19)

Hi =

√F 2i − (Z0+ δZi)

2, (20)

X0 =H1+H2+H3+H4

4cos

(D1+D2+D3+D4

4

)−δX1+ δX2+ δX3+ δX4

4, (21)

Y0 =H1+H2+H3+H4

4sin

(D1+D2+D3+D4

4

)−δY1+ δY2+ δY3+ δY4

4. (22)

A function (polynomial, cubic-spline, etc.) is then fittedon them. Finally, the magnetic vector is built according toEq. (2).

Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017 www.geosci-instrum-method-data-syst.net/6/361/2017/

A. Gonsette et al.: In situ vector calibration of magnetic observatories 365

Figure 3. LEMI-025 installed in the Dourbes magnetic observatory.The red arrow indicates the true north direction. The orange arrowshighlight the bubble-levels saturation.

202 202.5 203 203.5 204 204.5 205 205.5 20620 000

20 100

20 200

X0 [n

T]

Processed baseline versus raw baselines

RawProcessed

202 202.5 203 203.5 204 204.5 205 205.5 206150

200

250

300

Y0 [n

T]

202 202.5 203 203.5 204 204.5 205 205.5 206Day of year 2016

44 200

44 250

44 300

Z0 [n

T]

Figure 4. LEMi-025 baselines. Light blue: before processing. Darkblue: after processing.

4 Case study

A LEMI-025 variometer has been installed in the Dourbesmagnetic observatory. The device has deliberately been setup in a non-conventional orientation as shown in Fig. 3. Thelevelling and orientation error have been strongly exagger-ated compared to those encountered in conventional obser-vatories, but, if we consider a possible future automatic de-ployment using systems such as a GyroDIF (Gonsette et al.,2017), the orientation could be completely random. An Au-toDIF installed in the Dourbes absolute house has been usedfor performing absolute declination and inclination measure-ments because of its high-frequency measurement capability.An Overhauser magnetometer recorded the magnetic field in-tensity at the same time. One measurement every 30 min hasbeen made during 4 days from 20 to 24 July 2016. The meanKp index over this period is 2 while the maximum is 5 (onlythree periods of 3 h reached level 5 of the Kp index).

Before processing, the baseline computation clearly high-lights the set-up error as shown in Fig. 4. Actually, such bigvariations do not meet the international standards (St Louis,2012) and could discard the concerned magnetic observatory.Indeed, most observatories perform absolute D and I mea-surements no more than once a day, introducing an aliasingin the baseline computations. The amplitude of the baselinevariations in Fig. 4 is such that the 5 nT tolerated errors are

202 202.5 203 203.5 204 204.5 205 205.5 206-5

0

5

Xre

f-X*

[nT

] Magnetic components difference after processing

202 202.5 203 203.5 204 204.5 205 205.5 206-5

0

5

Yre

f-Y*

[nT

]

202 202.5 203 203.5 204 204.5 205 205.5 206Day of year 2016

-5

0

5

Zre

f-Z*

[nT

]

Figure 5. Variometer difference between a reference variometer andthe case study variometer. The value are clearly within 1 nT.

not met anymore. However, after solving the system for eachcomponents and applying the transformation matrix to thevariometer data, the baseline computation gives more correctdata. In this case, a cubic-spline function has been used forfitting to the baseline measurements.

A second LEMI-025 is installed in the variometer houseof the Dourbes observatory. This one is correctly set up, soit could be used for a posteriori comparison. Figure 5 showsthe difference between vector components built from the casestudy variometer and the reference variometer. Notice that,even if both are separated by as much as 10 m, the obser-vatory environment should ensure minimal difference. If weexclude the borders for which the cubic-spline baselines arebadly defined, the three curves meet the INTERMAGNET1 s standards requiring an absolute accuracy not worse than±2.5 nT. The Y andZ curves remain within±0.44 nT. TheXcomponent is slightly more noisy, with the upper and lowerborders being +1.11 and −0.38 nT respectively. The meandifferences are 0.06, 0.009 and 0.002 nT for X, Y and Zcurves respectively, and the corresponding standard devia-tions (1σ) are 0.26, 0.15 and 0.23 nT respectively.

5 Discussion

In this paper, the measurement errors have not been takeninto account. In particular, absolute measurements were per-formed sequentially so that the magnetic field could bechanged between the first and the last measurement. Equa-tions (12)–(14) do not take the variations between the meandeclination time and the mean inclination time into account.Indeed, using Eqs. (19)–(22) with the badly set up variometerfor compensating the magnetic activity would lead to a non-linear system. Nevertheless, AutoDIF achieves a completeprotocol of absolute measurement within less than 5 min in-cluding the geographic north measurement at the beginning.Because of the high number of measurements during a fewdays, the error due to this delay can be considered as ran-dom. Assuming that the measurement errors are a random

www.geosci-instrum-method-data-syst.net/6/361/2017/ Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017

366 A. Gonsette et al.: In situ vector calibration of magnetic observatories

noise, their effects are therefore cancelled according to theGauss–Markov theorem.

Jankowski and Sucksdorff (1996) suggested taking advan-tage of a disturbed day in order to maximise the effect of aset-up error. However, the global measurement noise may in-crease, in particular at high latitude. Indeed, the synchronisa-tion between instruments may become critical. Additionally,a rapid change in the magnetic field may induce soil currentthat could affect both the DI-flux instrument and the vari-ometer. Fortunately, as the noise is random and this is eventruer during chaotic magnetic activity, it has no effect on thefinal results.

Equation (16) supposes a constant baseline so that a smallvariation will contribute to the residues. However, the useof an automatic DI-flux instrument provides a large numberof measurements within a short time period. The case studyhas been performed during only 4 days, within which thebaseline variations are reasonably considered small. Theircontribution to the error can therefore be considered neg-ligible compared to the possible scale factor and orienta-tion parameter effects. Nevertheless, INTERMAGNET rec-ommends performing absolute measurements with an inter-val ranging from daily to weekly (St Louis, 2012).

6 Conclusions

The baselines and absolute measurements are powerful toolsfor checking data quality and for highlighting possible grosserrors. The present paper has demonstrated that even with astrong set-up error, it is possible to recover good magneticdata meeting the international standards. It also contributesto automatic installation and calibration of magnetic mea-surement systems. Future observatory deployments will bemore and more complex, with automatic dropped systems inunstable environments. The challenges of tomorrow are inAntarctica, the Earth’s seafloor or even Mars (Dehant et al.,2012). The application of theses methods will contribute toreaching those objectives. They will require not only auto-matic instruments but also regular and automatic control.

Data availability. Data are available upon request from the corre-sponding author at agonsett@meteo.be.

Competing interests. The authors declare that they have no conflictof interest.

Special issue statement. This article is part of the special issue“The Earth’s magnetic field: measurements, data, and applicationsfrom ground observations (ANGEO/GI inter-journal SI)”. It is a re-sult of the XVIIth IAGA Workshop on Geomagnetic ObservatoryInstruments, Data Acquisition and Processing, Dourbes, Belgium,4–10 September 2016.

Acknowledgements. We would like to acknowledge the RoyalMeteorological Institute of Belgium, which allowed this research.We also acknowledge the editor and the reviewers who contributedto the improvement of this article.

Edited by: Arnaud ChulliatReviewed by: Santiago Marsal and one anonymous referee

References

Alldregde, L. R.: A proposed Automatic Stan-dard Magnetic Observatory, J. Geophys. Res., 65,https://doi.org/10.1029/JZ065i011p03777, 1960.

Dehant, V., Banerdt, B. Lognonné, P., Grott, M., Asmar, S., Biele, J.,Breuer, D., Forget, F., Jaumann, R., Johnson, C., Knapmeyer, M.,Langlais, B., Le Feuvre, M., Mimoun, D., Mocquet, A., Read, P.,Rivoldini, A., Romberg, O., Schubert, G., Smrekar, S., Spohn, T.,Tortora, P., Ulamec, S., and Vennerstrom, S.: Future Mars geo-physical observatories for understanding its internal structure, ro-tation and evolution, Planet. Space Sci., 68, 123–145, 2012.

Eckstaller, A., Müller, C., Ceranna, L., and Hartmann, G.: Thegeophysics observatory at Neumayer stations (GvN and NM-II)Antarctica, Polarforschung, 76, 3–24, 2007.

Gonsette, A., Rasson, J., and Marin, J.-L.: Autodif: Automatic Ab-solute DI Measurements, Proceeding of the XVth IAGA Work-shop on Geomagnetic Observatory Instruments, data Acquisitionand Processing, 2012.

Gonsette, A., Rasson, J., Bracke, S., Poncelet, A., Hendrickx,O., and Humbled, F.: Automatic True North detection duringabsolute magnetic declination measurement, Geosci. Instrum.Method. Data Syst. Discuss., https://doi.org/10.5194/gi-2017-18,in review, 2017.

Jankowski, J. and Sucksdorff, C.: Guide for magnetic measurementsand observatory practice, Warsaw, IAGA, 1996.

Kerridge, D. J.: Theory of the Fluxgate-Theodolite, GeomagneticResearch Group Report 88/14, Edimburgh, British GeologicalSurvey, 1988.

Marusenkov, A., Chambodut, A., Schott, J.-J., and Korepanov,V.: Observatory magnetometer in-situ calibration, Data ScienceJournal, 10, https://doi.org/10.2481/dsj.IAGA-17, 2011.

Mohr, P. J., Newell, D. B., and Taylor, B. N.: CO-DATA recommended values of the fundamental phys-ical constants: 2014, Review of Modern Physics, 88,https://doi.org/10.1103/RevModPhys.88.035009, 2016.

Olsen, N., Toffner-Clausen, L., Sabaka, T. J., Brauer, P., Merayo, J.M. G., Jörgensen, J. L., Leger, J.-M., Nielsen, O. V., Primdahl,F., and Risbo, T.: Calibration of the Orsted vector magnetometer,Earth Planet. Space, 55, 11–18, 2003.

Rasson, J. L.: About Absolute Geomagnetic Measurements in theObservatory and in the Field, Publication scientifique et tech-nique no 40, Institut Royal Météorologique, 2005.

St Louis, B. (Ed.): INTERMAGNET technical reference man-ual: Version 4.6, 92 pp., available at: http://intermagnet.org/publications/intermag_4-6.pdf (last access: 7 February 2017),2012.

Geosci. Instrum. Method. Data Syst., 6, 361–366, 2017 www.geosci-instrum-method-data-syst.net/6/361/2017/

https://doi.org/10.1029/JZ065i011p03777https://doi.org/10.5194/gi-2017-18https://doi.org/10.2481/dsj.IAGA-17https://doi.org/10.1103/RevModPhys.88.035009http://intermagnet.org/publications/intermag_4-6.pdfhttp://intermagnet.org/publications/intermag_4-6.pdf

AbstractIntroductionCalibration error detectionScale factor errorOrientation error

Calibration processCase studyDiscussionConclusionsData availabilityCompeting interestsSpecial issue statementAcknowledgementsReferences