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GOES Particle Intracalibration Toolkit

GOES Particle Intracalibration Toolkit

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GOES Particle Intracalibration Toolkit

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  1. GOES Particle Intracalibration Toolkit William Rowland NOAA/NESDIS/STAR, GMU Robert Weigel, PhD George Mason University Changyong Cao, PhD NOAA/NESDIS/STAR

  2. GOES MAGED Sensor

  3. GOES NOP SEM Instruments

  4. Coordinate System

  5. EPS HEPAD Handbook

  6. MAGED • Solid State Detector, collimator, and electronics • Determines energy of electrons based on energy deposited. • Energy range in table below. GOES-NOP Data book


  8. GOES MAGED Energy Captured EPS HEPAD Handbook

  9. State of GOES Calibration

  10. Pre-launch • Initial factors determined during ground calibration. • No standards between beamlines • Full energy/flux range may not be calibrated • Only one telescope generally characterized

  11. On-orbit • In-flight Calibration • Should track electronics degradation • Not useful in some channels of current generation • Currently not performed even for useful channels • During Post-Launch testing comparisons are sometimes performed • Between telescopes on a single GOES satellite • Between GOES satellites

  12. On-orbit (continued) • After Post-launch testing • Generally no resources have been devoted to following changes in cal factors due to different rates of degradation • Neither SWPC nor NSOF has the resources necessary

  13. Objectives for Future GOES Calibration

  14. STAR’s Role • Stewards of L1b Data Quality • Analyze and trend performance of instruments • Recommend adjustments to calibration factors as necessary • Participate in anomaly resolution as necessary • Limited manpower necessitates development of tools • GOES Particle Intercalibration Toolkit • Permit intracalibration of telescopes aboard the same satellite. • Permit intercalibration of satellites. • Make the data obtained publicly available, so that others involved in the process (like NSOF) and the user community can track performance as desired.

  15. Why use Pitch Angle to identify intracalibration data?

  16. Phase space consists of 3 position vectors, 3 velocity vectors, a scalar number density. • Phase space coordinates express this in terms of 3 adiabatic invariants (μ, K, L*), 3 phases, and a scalar. • For intracalibration • Position is the same for all telescopes on a satellite. • K and L* depend on the magnetic field. All telescopes are in the same magnetic field.

  17. Chen et. al, 2005

  18. First Adiabatic invariant defines • Where

  19. B1=B2, vTot1~VTot2, m1 = m2 • Therefore, if α1=α2 then μ1= μ2 • In this case all adiabatic invariants are the same for the particles measured by the two telescopes. • These data may be useful for calibration.

  20. Selection Criteria for Data

  21. Calculate representative pitch angles using • Magnetic Field measurements • Knowledge of the orientation of the particle sensors • Currently spacecraft reference frame is utilized • Any common frame works

  22. Pitch Angle “match” is defined as the angles matching to within 1 degree. • Particle sensor orientation knowledge is no better. • This may be overly restrictive • Less stringent requirements yielded visually similar results, at least to several degrees

  23. Additional constraints • Magnetic field vector direction changing quickly • Necessary for the First Adiabatic Invariant to be meaningful • Used a limit of 1 degree per integration cycle for the current plots • Parameter is included in metadata • User can view different results if desired

  24. Additional constraints or possible confounds which are being considered • Dst values • Did not appear to make a large difference • Rate of change in count rates • Have not examined the current data set to see if an impact is noticeable. • Local time • Have not examined data set for impact • This may have more of an impact at lower energies (S/C charging)

  25. Toolkit Results

  26. Toolkit Results Statistics

  27. Statistics for data from beginning of May 2010 to end of July 2010

  28. Toolkit Development Status

  29. Current tasks • Quantify impact of additional effects • Dst, changes in count rate, local time, etc… • Obtain further peer review • Automate code • Currently can manually order it to retrieve and analyze a month’s worth of data • Make results available to SWPC • STAR does not have a mandate to calibrate GOES-NOP

  30. Software issues • File sizes are getting too large. Need to either • Optimize code • Change platforms • Bundle datasets into 3 month sets