** Progress in Earth and Planetary Science is the official journal of the Japan Geoscience Union, published in collaboration with its 51 society members.

    ** Progress in Earth and Planetary Science is partly financially supported by a Grant-in-Aid for Publication of Scientific Research Results to enhance dissemination of information of scientific research.

    >>Japan Geoscience Union

    >>Links to 51 society members

    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    Progress in Earth and Planetary Science

    Gallery View of PEPS Articles

    Research

    Space and planetary sciences

    201803201803

    Daily and seasonal variations in the linear growth rate of the Rayleigh-Taylor instability in the ionosphere obtained with GAIA

    Shinagawa H, Jin H, Miyoshi Y, Fujiwara H, Yokoyama T, Otsuka Y

    Equatorial plasma bubble, Occurrence rate, Daily variation, Atmosphere-ionosphere coupled model, Rayleigh-Taylor instability, Linear growth rate

    Daily variations in R-T growth rate obtained with GAIA.

    The linear growth rates of the Rayleigh-Taylor (R-T) instability in the ionosphere from 2011 to 2013 were obtained with a whole atmosphere-ionosphere coupled model GAIA (ground-to-topside model of atmosphere and ionosphere for aeronomy). The effects of thermospheric dynamics driven by atmospheric waves propagating from below on the R-T growth rate are included in the model by incorporating meteorological reanalysis data in the region below 30 km altitude. The daily maximum R-T growth rates for these periods are compared with the observed occurrence days of the equatorial plasma bubble (EPB) determined by the Equatorial Atmosphere Radar (EAR) and Global Positioning System (GPS) in West Sumatra, Indonesia. We found that a high R-T growth rate tends to correspond to the actual EPB occurrence, suggesting the possibility of predicting EPB occurrences with numerical models.