JpGU-AGU Joint Meeting 2020

Presentation information

[E] Poster

P (Space and Planetary Sciences ) » P-EM Solar-Terrestrial Sciences, Space Electromagnetism & Space Environment

[P-EM18] Study of coupling processes in solar-terrestrial system

convener:Mamoru Yamamoto(Research Institute for Sustainable Humanosphere, Kyoto University), Yasunobu Ogawa(National Institute of Polar Research), Satonori Nozawa(Institute for Space-Earth Environmental Research, Nagoya University), Akimasa Yoshikawa(Department of Earth and Planetary Sciences, Kyushu University)

[PEM18-P11] Study of atmospheric stability in the polar upper mesosphere and lower thermosphere above Tromsø by using sodium LIDAR data

*Sakiho Maeda1, Satonori Nozawa1, Takuya Kawahara2, Norihito Saito3, Takuo T. Tsuda4, Satoshi Wada3, Toru Takahashi5, Tetsuya Kawabata1, Chris Hall6 (1.Institute for Space-Earth Environmental Research, Nagoya University, 2.Faculty of Engineering, Shinshu University, 3.RIKEN Center for Advanced Photonics, RIKEN, 4.The University of Electro-Communications, 5.Department of Physics, University of Olso, 6.UiT The Arctic University of Norway)

We will report atmospheric stability in the polar upper Mesosphere and Lower Thermosphere (MLT) region (80-105 km) above Tromsø, Norway (69.6°N, 19.2°E) based on 2500 hours of sodium LIDAR data.

We have analyzed temperature and velocity data (6 min and 0.5 km resolutions) obtained over 8 seasons from October 2012 to March 2019 (about 2500 hour measurements of 237 nights). We have evaluated both static (convective) instability and dynamic (shear) instability using the square of Brunt–Väisälä frequency (N2) and Richardson number (Ri), respectively. Furthermore, we have calculated the instability probability defined as the percentage of an occurrence rate of unstable regions over the time interval. The probabilities of static instability and dynamic instability are shown as P(N2 < 0) and P(0 < Ri < 1/4), respectively. The temperature data and wind data are used to calculate N and wind shear (dv/dz), respectively.

We have found that P(N2 < 0) varies from a maximum of 20.6 % to a minimum of 0.5 %, and P(0 < Ri < 1/4) varies from a maximum of 14 % to a minimum of 1.6% in the altitude region between 85 km to 95 km. P(N2 < 0) tends to be larger than P(0 < Ri < 1/4). These probabilities do not show any obvious monthly variations from October to March, rather day-to-day variabilities are prominent. As shown in Figure 1, over the entire period, P(N2 < 0) at around 90 km altitude tends to be lower than those at around 80 km and 100 km: the static instability was less likely to occur at around 90 km. There is a weak correlation between P(0 < Ri < 1/4) and the semidiurnal tidal amplitude, but no correlation between P(N2 < 0) and the semidiurnal tidal amplitude is found.

Based on these observational results, we will present the characteristics of the atmospheric stabilities in the polar winter MLT region above Tromsø. Furthermore, the results will be compared with those in mid-latitude.