Geocoronal Hα intensity measurements using the Wisconsin Hα Mapper Fabry-Perot facility

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Atmospheric Composition And Structure: Airglow And Aurora, Atmospheric Composition And Structure: Thermosphere-Composition And Chemistry

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The Wisconsin Hα Mapper (WHAM), a remotely operable, semi-automated Fabry-Perot located at Kitt Peak Observatory, has been making an all-sky survey of interstellar hydrogen Balmer α (Hα) emissions since 1997. Using the annular summing spectroscopy technique, WHAM has acquired ~37,000 spectra to date, spanning almost 100 nights of observations. Since all of the galactic emission spectral data contain the terrestrial Hα (6562.7 Å) emission line, these measurements constitute a rich source of geocoronal data for investigating natural variability in the upper atmosphere. The WHAM observations also serve as a benchmark for comparison with future data. Analysis of the first year of WHAM data shows only small day-to-day variations after shadow altitude variations are taken into account. For example, at shadow altitudes of 2000 and 3000 km, the RMS scatter is within approximately +/- 20% this variability is expected to be reduced with accurate accounting of the smaller-scale effects of observational slant path, zenith angle, and azimuth on the Hα intensity. This result is consistent with past midlatitude Wisconsin data sets but different from observations made by other observers and instruments at the low-latitude Arecibo site. The multiple viewing geometries of the observations provide stringent modeling constraints, useful in testing current modeling capabilities. Modeling of the WHAM data with a global nonisothermal resonance radiation transport code (lyao_rt) indicates that the signal-to-noise of the data is sufficient to determine relative variations in upper atmospheric atomic hydrogen column densities to better than 5%. This paper describes the WHAM aeronomy program and its observational scheme, analysis procedures, and results from data taken in 1997. Case study comparisons are made with past data sets and with predictions from the lyao_rt resonant radiation transport modeling code of Bishop [1999].

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