14:15 〜 14:30
[AAS21-14] SMILESデータを用いた中層大気科学についての最近の成果
キーワード：Middle Atmosphere, Ozone, Satellite Observation
The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) aboard the Japanese Experiment Module (JEM) of the International Space Station (ISS) made atmospheric measurements of minor species in the stratosphere and mesosphere for about six months from October 2009 to April 2010. Data for scientific community are now provided from DARTS (Data ARchives and Transmission System) of ISAS/JAXA (http://darts.isas.jaxa.jp/iss/smiles/). In this talk, we will present recent results from the SMILES measurements in association with middle atmospheric chemistry and dynamics. The main topics to be highlighted are as follows. [Diurnal ozone variations in the stratosphere] The SMILES observations have revealed the global pattern of diurnal ozone variations throughout the stratosphere. The peak-to-peak difference in the stratospheric ozone mixing ratio reaches 8% over the course of a day, suggesting careful consideration when merging ozone data from different satellite measurements (Sakazaki et al., 2013).[Ozonesonde bias suggested from comparisons with SMILES] The SMILES ozone data have been extensively compared with other satellite data sources (Imai et al., 2013a). Further comparisons of SMILES ozone profiles with those from ozonesondes show that the agreement was generally good, but at low latitudes the SMILES ozone data showed larger values than those at middle and high latitudes. To explain this bias, we examined an issue of the ozonesonde's response time, and found a negative bias in ozonesonde measurements more than 7% at 20 km in the equatorial latitude (Imai et al., 2013b). [Mesospheric ozone variations during the solar eclipse] During the annular solar eclipse on 15 January 2010, SMILES successfully captured temporal changes in ozone concentration. We found that in the lower mesosphere ozone amounts get closer to the normal nighttime average, and the mechanism is detailed with use of an atmospheric chemistry box model (Imai et al., 2014).