Testing an inversion method for estimating electron energy fluxes from all-sky camera images

An inversion method for reconstructing the pre- cipitating electron energy flux from a set of multi-wavelength digital all-sky camera (ASC) images has recently been devel- oped by Janhunen (2001). Preliminary tests suggested that the inversion is able to reconstruct the position and energy characteristics of the aurora with reasonable accuracy. This study carries out a thorough testing of the method and a few improvements for its emission physics equations. We compared the precipitating electron energy fluxes as estimated by the inversion method to the energy flux data recorded by the Defense Meteorological Satellite Program (DMSP) satellites during four passes over auroral structures. When the aurorae appear very close to the local zenith, the fluxes inverted from the blue (427.8 nm) filtered ASC im- ages or blue and green line (557.7 nm) images together give the best agreement with the measured flux values. The fluxes inverted from green line images alone are clearly larger than the measured ones. Closer to the horizon the quality of the inversion results from blue images deteriorate to the level of the ones from green images. In addition to the satellite data, the precipitating electron energy fluxes were estimated from the electron density measurements by the EISCAT Svalbard Radar (ESR). These energy flux values were compared to the ones of the inversion method applied to over 100 ASC im- ages recorded at the nearby ASC station in Longyearbyen. The energy fluxes deduced from these two types of data are in general of the same order of magnitude. In 35% of all of the blue and green image inversions the relative errors were less than 50% and in 90% of the blue and green image inver- sions less than 100%. This kind of systematic testing of the inversion method is the first step toward using all-sky camera images in the way in which global UV images have recently been used to esti- mate the energy fluxes. The advantages of ASCs, compared to the space-born imagers, are their low cost, good spatial resolution and the possibility of continuous, long-term mon- itoring of the auroral oval from a fixed position.

[1]  M. Rees,et al.  Auroral ionization and excitation by incident energetic electrons , 1963 .

[2]  D. Luckey,et al.  Auroral electron energy derived from ratio of spectroscopic emissions 1. Model computations , 1974 .

[3]  T. Hallinan.  Auroral spirals 2. Theory , 1976 .

[4]  Wolfgang Baumjohann,et al.  JOINT TWO-DIMENSIONAL OBSERVATIONS OF GROUND MAGNETIC AND IONOSPHERIC ELECTRIC FIELDS ASSOCIATED WITH AURORAL ZONE CURRENTS: CURRENT SYSTEMS ASSOCIATED WITH LOCAL AURORAL BREAK-UPS , 1981 .

[5]  D. Hardy.  Precipitating electron and ion detectors (SSJ/4) for the block 5D/flights 6-10 DMSP satellites: calibration and data presentation , 1984 .

[6]  S. Franke,et al.  Application of computerized tomography techniques to ionospheric research , 1986 .

[7]  A. Hedin.  MSIS‐86 Thermospheric Model , 1987 .

[8]  B. Lanchester,et al.  Field-aligned current reversals and fine structure in a dayside auroral arc , 1987 .

[9]  S. Kirkwood.  SPECTRUM: A computer algorithm to derive the flux-energy spectrum of precipitating particles from EISCAT electron density profiles , 1988 .

[10]  M. Rees.  Physics and Chemistry of the Upper Atmosphere , 1989 .

[11]  J. Klobuchar,et al.  Application of computerized tomography to the investigation of ionospheric structures , 1990 .

[12]  A. Hedin.  Extension of the MSIS Thermosphere Model into the middle and lower atmosphere , 1991 .

[13]  E. Andreeva,et al.  Phase-difference radiotomography of the ionosphere , 1992 .

[14]  V. E. Ivanov,et al.  A new approach to calculate the excitation of atmospheric gases by auroral electron impact , 1993 .

[15]  E. Bering,et al.  Particle and field signatures during pseudobreakup and major expansion onset , 1994 .

[16]  O. Amm.  Direct determination of the local ionospheric Hall conductance distribution from Two‐dimensional electric and magnetic field data: Application of the method using models of typical ionospheric electrodynamic situations , 1995 .

[17]  G. Haerendel,et al.  Auroral emission profiles extracted from three‐dimensionally reconstructed arcs , 1996 .

[18]  H. Opgenoorth,et al.  Particle precipitation in auroral breakups and westward traveling surges , 1996 .

[19]  Harald U. Frey,et al.  Three-dimensional reconstruction of the auroral arc emission from stereoscopic optical observations , 1996, Optics & Photonics.

[20]  M. Lehtinen,et al.  Application of stochastic inversion in auroral tomography , 1996 .

[21]  H. Frey,et al.  Optical tomography of the aurora and EISCAT , 1998 .

[22]  T. Pulkkinen,et al.  Observations of Substorm Electrodynamics Using the MIRACLE Network , 1998 .

[23]  O. Amm.  Method of characteristics in spherical geometry applied to a Harang-discontinuity situation , 1998 .

[24]  B. Gustavsson.  Tomographic inversion for ALIS noise and resolution , 1998 .

[25]  V. Angelopoulos,et al.  Characteristics of pseudobreakups and substorms observed in the ionosphere, at the geosynchronous orbit, and in the midtail , 1999 .

[26]  K. Kaila,et al.  Absolute calibration of photometer , 2000 .

[27]  K. Kauristie,et al.  Characteristics of a stable are based on FAST and MIRACLE observations , 2000 .

[28]  R. Hoffman,et al.  Erratum: ``Height-integrated conductivity in auroral substorms, 1, Data'' , 2000 .

[29]  T. Pulkkinen,et al.  Statistical study of auroral spirals , 2001 .

[30]  T. Pulkkinen,et al.  Mesoscale ionospheric electrodynamics observed with the MIRACLE network: 1. Analysis of a pseudobreakup spiral , 2001 .

[31]  P. Janhunen.  Reconstruction of electron precipitation characteristics from a set of multiwavelength digital all‐sky auroral images , 2001 .

[32]  L. Oikarinen.  Polarization of light in UV‐visible limb radiance measurements , 2001 .