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At least 37 records · Page 2

Triaxial digital fluxgate magnetometer for NASA applications explorer mission: Results of tests of critical elements

Tests performed to prove the critical elements of the triaxial digital fluxgate magnetometer design were described. A method for improving the linearity of the analog to digital converter portion of the instrument was studied in detail. A sawtooth waveform was added to the signal being measured before the A/D conversion, and averaging the digital readings over one cycle of the sawtooth. It was intended to reduce bit error nonlinearities present in the A/D converter which could be expected to be as much as 16 gamma if not reduced. No such nonlinearities were detected in the output of the instrument which included the feature designed to reduce these nonlinearities. However, a small scale nonlinearity of plus or minus 2 gamma with a 64 gamma repetition rate was observed in the unit tested. A design improvement intended to eliminate this small scale nonlinearity was examined.

Mcleod, M. G.↗

The MAGSAT vector magnetometer: A precision fluxgate magnetometer for the measurement of the geomagnetic field

A description of the precision triaxial fluxgate magnetometer to be flown aboard the MAGSAT spacecraft is presented. The instrument covers the range of + or - 64,000 nT with a resolution of + or - 0.5 nT, an intrinsic accuracy of + or - 0.001% of full scale and an angular alignment stability of the order of 2 seconds of arc. It was developed at NASA's Goddard Space Flight Center and represents the state-of-the-art in precision vector magnetometers developed for spaceflight use.

Acuna, M. H.↗

Induced electric currents in the Alaska oil pipeline measured by gradient, fluxgate, and SQUID magnetometers

The field gradient method for observing the electric currents in the Alaska pipeline provided consistent values for both the fluxgate and SQUID method of observation. These currents were linearly related to the regularly measured electric and magnetic field changes. Determinations of pipeline current were consistent with values obtained by a direct connection, current shunt technique at a pipeline site about 9.6 km away. The gradient method has the distinct advantage of portability and buried- pipe capability. Field gradients due to the pipe magnetization, geological features, or ionospheric source currents do not seem to contribute a measurable error to such pipe current determination. The SQUID gradiometer is inherently sensitive enough to detect very small currents in a linear conductor at 10 meters, or conversely, to detect small currents of one amphere or more at relatively great distances. It is fairly straightforward to achieve imbalance less than one part in ten thousand, and with extreme care, one part in one million or better.

Campbell, W. H.↗

The IRM fluxgate magnetometer

This report describes the three-axis fluxgate magnetometer instrument on board the AMPTE IRM spacecraft. Important features of the instrument are its wide dynamic range (0.1-60,000 nT), a high resolution (16-bit analog to digital conversion) and the capability to operate automatically or via telecommand in two gain states. In addition, the wave activity is monitored in all three components up to 50 Hz. Inflight checkout proved the nominal functioning of the instrument in all modes.

Luehr, H.↗

In-Flight Calibration Processes for the MMS Fluxgate Magnetometers

The calibration effort for the Magnetospheric Multiscale Mission (MMS) Analog Fluxgate (AFG) and DigitalFluxgate (DFG) magnetometers is a coordinated effort between three primary institutions: University of California, LosAngeles (UCLA); Space Research Institute, Graz, Austria (IWF); and Goddard Space Flight Center (GSFC). Since thesuccessful deployment of all 8 magnetometers on 17 March 2015, the effort to confirm and update the groundcalibrations has been underway during the MMS commissioning phase. The in-flight calibration processes evaluatetwelve parameters that determine the alignment, orthogonalization, offsets, and gains for all 8 magnetometers usingalgorithms originally developed by UCLA and the Technical University of Braunschweig and tailored to MMS by IWF,UCLA, and GSFC. We focus on the processes run at GSFC to determine the eight parameters associated with spin tonesand harmonics. We will also discuss the processing flow and interchange of parameters between GSFC, IWF, and UCLA.IWF determines the low range spin axis offsets using the Electron Drift Instrument (EDI). UCLA determines the absolutegains and sensor azimuth orientation using Earth field comparisons. We evaluate the performance achieved for MMS andgive examples of the quality of the resulting calibrations.

Electromagnetic field Measurements↗

In-Flight Calibration Methods for Temperature-Dependent Offsets in the MMS Fluxgate Magnetometers

During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection↗

In-Flight Calibration of the MMS Fluxgate Magnetometers

We present an overview of the approach to in-flight calibration, which is a coordinated effort between the University of California Los Angeles (UCLA), Space Research Institute, Graz, Austria (IWF) and the NASA Goddard Space Flight Center (GSFC). We present details of the calibration effort at GSFC. During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection↗

Crucial Role of Thermal Gradients in MMS Fluxgate In-Flight Calibration

To meet the science goals of the Magnetospheric Multiscale (MMS) mission, the Fluxgate Magnetometer (FGM) must measure the ambient magnetic field with an accuracy of 0.1 nT. On a typical MMS orbit, the offsets (or zero levels) of the 3-axis FGM can vary by ~0.5 nT (exclusive of periods in Earth shadow). Previous studies have shown that these variations can be characterized as functions of sensor temperature, TS, and can thus be corrected to within 0.2 nT in the spin plane using in-flight calibration techniques (Bromund, et al., 2016, https://ntrs.nasa.gov/citations/20160014711). In that presentation, we noted two significant observations: A distinct function of TS must be used to characterize offsets during shadow: offsets at a given TScan differ by as much as 2 nT in shadow vs sunlight. Offsets change after maneuvers, without a commensurate change in TS . These changes can be as large as 2 nT. We now note a third, related observation: Offsets increase with proximity to the earth even when TS is constant, resulting in variations of ~0.2 nT at 4-5 Earth radii (RE) These effects are evidence that offsets are a multivariate function of TS and another factor, namely: thermal gradients. Due to the spacecraft spin, the Earth and the Sun each provide a relatively constant thermal input onto one instrument face while the opposite face remains in shadow, thus giving rise to thermal gradients. The thermal gradient depend on the orientation of the spin axis relative to the Earth or Sun. We observe that offsets vary by as much as 0.17 nT/degree as a function of the tilt of the spin axis towards the Sun. Thermal input from the Earth is dominated by Outgoing Longwave Radiation (OLR). Due to the proximity to Earth, the inverse proportion of the distance squared is a significant factor in the thermal gradient attributed to Earth OLR. We find that offsets can be corrected to <0.05 nT accuracy near perigee when accounting for these factors using empirically determined constants of proportionality that account for differences in emissivity of the top and bottom faces of the sensor to OLR (as well as other thermal effects). The changes in offset associated with thermal gradient are of the same order of magnitude as effects that were formerly attributed to sensor temperature alone, and thus both parameters are necessary to characterize the FGM offsets.

Kenneth R Bromund↗

The theoretical output of a ring core fluxgate sensor.

Demonstration that the output from a ring core sensor is directly proportional to the first time derivative of the product of dynamic permeability and magnetic intensity perturbation within the core caused by an external, uniform magnetic field. (Dynamic permeability is defined to be the slope of the hysteresis loop at a given point in time). Assuming that ellipsoidal shells can approximate the core, the demagnetization factor can be 'estimated' in the first order to be proportional to the first power of the quantity tape thickness (or number of wraps) divided by the core diameter. The constant of proportionality is determined from laboratory data. When an additional scale adjustment is applied to the resulting sensor output formula, the computed output tracks laboratory data for a range of sensor geometries.

Burger, J. R.↗

Vector magnetometer design study: Analysis of a triaxial fluxgate sensor design demonstrates that all MAGSAT Vector Magnetometer specifications can be met

The design of the vector magnetometer selected for analysis is capable of exceeding the required accuracy of 5 gamma per vector field component. The principal elements that assure this performance level are very low power dissipation triaxial feedback coils surrounding ring core flux-gates and temperature control of the critical components of two-loop feedback electronics. An analysis of the calibration problem points to the need for improved test facilities.

Adams, D. F.↗

SSA-A spacecraft magnetic tests

In the initial magnetic tests the spacecraft perm moment as received was 43 milliampere-meter squared (pole-cm), which was reduced by deperm treatment to milliampere-meter squared. Facility fluxgate probe bias results indicated Z axis bias at the SSS-A fluxgate magnetometer position to be about one half nanotesla (gamma) after Z axis deperm. The ASCS magnetometers, 01 and 02, were successfully aligned and proper operation of the ASCS system were verified. The spacecraft fluxgate magnetometer was calibrated in both the high and low sensitivity modes after a defective 01 electronics card was replaced. Problems were encountered in the Z axis search coil during calibration and the test was re-scheduled. Final test results indicated that the total perm moment could not be reduced any lower than 35 milliampere-meter squared by deperm treatment. However, the Z axis moment decreased from 22 milliampere-meter squared to 6 milliampere-meter squared after deperm. Correct operation and calibration was verified for all three axes of the spacecraft fluxgate magnetometer and no significant bias was observed during stray field testing. Null and spot calibration of the ASCS magnetometer was completed and the measured spin and attitude coil moments were: 2535 and 9820 milliampere-meter squared respectively.

Roy, T. N.↗

System and Method for an Integrated Satellite Platform

A system, method, and computer-readable storage devices for a 6U CubeSat with a magnetometer boom. The example 6U CubeSat can include an on-board computing device connected to an electrical power system, wherein the electrical power system receives power from at least one of a battery and at least one solar panel, a first fluxgate sensor attached to an extendable boom, a release mechanism for extending the extendable boom, at least one second fluxgate sensor fixed within the satellite, an ion neutral mass spectrometer, and a relativistic electron/proton telescope. The on-board computing device can receive data from the first fluxgate sensor, the at least one second fluxgate sensor, the ion neutral mass spectrometer, and the relativistic electron/proton telescope via the bus, and can then process the data via an algorithm to deduce a geophysical signal.

Clagett, Charles E.↗

AMR Magnetic Sensors in Flux Expulsion Studies

Magnetic flux expulsion properties of the superconducting material such as bulk niobium, widely used for the radio-frequency cavity fabrication, substantially affect the performance characteristics of the cavities. The quality factor of the SRF resonators can be significantly compromised due to the presence of the trapped flux vortices causing additional RF energy losses in the material. Large number of experiments have been carried out by different research groups to establish the correlation of the flux trapping in niobium cavities with the presence of impurities in niobium as well as various surface treatment methods. Majority of these experiments utilize commercially available cryogenic fluxgate magnetic sensors to measure the field before and after the niobium transition to the superconducting state to quantify the amount of flux trapped. One disadvantage of the typically used fluxgates is the size of the sensing volume. As an example, the Barting-ton F and G type cryogenic fluxgates have a sensing core length of about 30mm, which is comparable to the curvature radius of the cavity walls and hence the magnetic field lines curvature radius after the expulsion. Thus, the measured field value needs to be corrected to account for the sensor effective averaging over the sensing volume. In case of the sharper geometries, for instance if the flux expulsion to be measured on the edge of the rectangular niobium flat sheet with a thickness of ~5mm, the use of the fluxgate would be impractical.

Netepenko, A.↗

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

The magnetic field of Saturn - Pioneer 11 observations

The Pioneer 11 high-field fluxgate magnetometer experiment consists of two biaxial fluxgate sensors assemblies and an associated electronics system that is designed to measure fields up to 10 gauss along three orthogonal axes. It was used to provide a higher upper range than that provided by the helium vector magnetometer whose maximum measureable field is only 1.4 gauss. Observations of the intrinsic magnetic field of Saturn measured by the high-field fluxgate magnetometer were found to be much weaker than expected. An analysis of preliminary data combined with the preliminary trajectory yield a model for the main planetary field which is a simple centered dipole. It was determined that the polarity of Saturn is opposite that of Earth, and that the tilt is small, within 2 deg plus or minus 1 deg.

Acuna, M. H.↗

Lunar surface magnetometers

Discussion of the properties of both the stationary and portable magnetometers used in the Apollo program to measure static and dynamic fields on the lunar surface. A stationary magnetometer is described in which the three orthogonal vector components of the magnetic field are measured by three fluxgate sensors which are located at the ends of three orthogonal booms and contain ferromagnetic cores driven to saturation by means of a periodic current. In the Apollo 16 magnetometer special high-stability ring-core sensors were used which provided an output voltage to the analog-to-digital converter which is proportional to the magnetic field. A portable magnetometer is described which consists of a set of three orthogonal fluxgate sensors mounted on top of a tripod connected to an electronics box by a ribbon cable. The above-mentioned stationary magnetometer simultaneously measured the time-varying components of the field which were later subtracted from the portable magnetometer measurements to give the desired resultant steady field values caused by the magnetized crustal material.

Dyal, P.↗

Early results from Magsat

Papers presented at the May 27, 1981 meeting of the American Geophysical Union concerning early results from the Magsat satellite program, which was designed to study the near-earth magnetic fields originating in the core and lithosphere, are discussed. The satellite was launched on October 30, 1979 into a sun-synchronous (twilight) orbit, and re-entered the atmosphere on June 11, 1980. Instruments carried included a cesium vapor magnetometer to measure field magnitudes, a fluxgate magnetometer to measure field components and an optical system to measure fluxgate magnetometer orientation. Early results concerned spherical harmonic models, fields due to ionospheric and magnetospheric currents, the identification and interpretation of fields from lithospheric sources. The preliminary results confirm the possibility of separating the measured field into core, crustal and external components, and represent significant developments in analytical techniques in main-field modelling and the physics of the field sources.

Langel, R. A.↗