TY - JOUR

T1 - A statistical study of convective and dynamic instabilities in the polar upper mesosphere above Tromsø

AU - Nozawa, Satonori

AU - Saito, Norihito

AU - Kawahara, Takuya

AU - Wada, Satoshi

AU - Tsuda, Takuo T.

AU - Maeda, Sakiho

AU - Takahashi, Toru

AU - Fujiwara, Hitoshi

AU - Narayanan, Viswanathan Lakshmi

AU - Kawabata, Tetsuya

AU - Johnsen, Magnar G.

N1 - S.N. thanks Dr. K. Hocke for letting to use his Lomb-Scargle periodogram method routines. The local K-index is provided by TGO, UiT The Arctic University of Tromsø. We thank the EISCAT staff for supporting the lidar observations.
Funding Information:
This research has been partly supported by a Grant-in-Aid for Scientific Research A (21H04516, 21H04518) and B (17H02968, 19H01952, 21H01142, 21H01144), and a Grant-in-Aid for Exploratory Research (20K20940). This work is partially supported by Nagoya University Research Fund. VL Narayanan is supported by the Natural Environment Research Council (NERC), UK (grant no. NE/V01837X/1).
Availability of data and materials
All data generated or analyzed during this study are available at https://www.
isee.nagoya-u.ac.jp/~nozawa/indexlidardata.html; https://spaceweather.gc.ca/
solarfux/sx-5-en.php; https://fux.phys.uit.no/Kindice/.

PY - 2023/2/15

Y1 - 2023/2/15

N2 - We have studied the convective (or static) and dynamic instabilities between 80 and 100 km above Tromsø (69.6° N, 19.2° E) using temperature and wind data of 6 min and 1 km resolutions primarily almost over a solar cycle obtained with the sodium lidar at Tromsø. First, we have calculated Brunt–Väisälä frequency (N) for 339 nights obtained from October 2010 to December 2019, and the Richardson number (Ri) for 210 nights obtained between October 2012 to December 2019. Second, using those values (N and Ri), we have calculated probabilities of the convective instability (N2 < 0) and the dynamic instability (0 ≤ Ri < 0.25) that can be used for proxies for evaluating the atmospheric stability. The probability of the convective instability varies from about 1% to 24% with a mean value of 9%, and that of the dynamic instability varies from 4 to 20% with a mean value of 10%. Third, we have compared these probabilities with the F10.7 index and local K-index. The probability of the convective instability shows a dependence (its correlation coefficient of 0.45) of the geomagnetic activity (local K-index) between 94 and 100 km, suggesting an auroral influence on the atmospheric stability. The probability of the dynamic instability shows a solar cycle dependence (its correlation coefficient being 0.54). The probability of the dynamic instability shows the dependence of the 12 h wave amplitude (meridional and zonal wind components) (C.C. = 0.52). The averaged potential energy of gravity waves shows decrease with height between 81 and 89 km, suggesting that dissipation of gravity waves plays an important role (at least partly) in causing the convective instability below 89 km. The probability of the convective instability at Tromsø appears to be higher than that at middle/low latitudes, while the probability of the dynamic instability is similar to that at middle/low latitudes. Graphical Abstract: [Figure not available: see fulltext.]

AB - We have studied the convective (or static) and dynamic instabilities between 80 and 100 km above Tromsø (69.6° N, 19.2° E) using temperature and wind data of 6 min and 1 km resolutions primarily almost over a solar cycle obtained with the sodium lidar at Tromsø. First, we have calculated Brunt–Väisälä frequency (N) for 339 nights obtained from October 2010 to December 2019, and the Richardson number (Ri) for 210 nights obtained between October 2012 to December 2019. Second, using those values (N and Ri), we have calculated probabilities of the convective instability (N2 < 0) and the dynamic instability (0 ≤ Ri < 0.25) that can be used for proxies for evaluating the atmospheric stability. The probability of the convective instability varies from about 1% to 24% with a mean value of 9%, and that of the dynamic instability varies from 4 to 20% with a mean value of 10%. Third, we have compared these probabilities with the F10.7 index and local K-index. The probability of the convective instability shows a dependence (its correlation coefficient of 0.45) of the geomagnetic activity (local K-index) between 94 and 100 km, suggesting an auroral influence on the atmospheric stability. The probability of the dynamic instability shows a solar cycle dependence (its correlation coefficient being 0.54). The probability of the dynamic instability shows the dependence of the 12 h wave amplitude (meridional and zonal wind components) (C.C. = 0.52). The averaged potential energy of gravity waves shows decrease with height between 81 and 89 km, suggesting that dissipation of gravity waves plays an important role (at least partly) in causing the convective instability below 89 km. The probability of the convective instability at Tromsø appears to be higher than that at middle/low latitudes, while the probability of the dynamic instability is similar to that at middle/low latitudes. Graphical Abstract: [Figure not available: see fulltext.]

KW - Brunt–Väisälä frequency

KW - Convective instability

KW - Dynamic instability

KW - Gravity wave dissipation

KW - Polar upper mesosphere

KW - Richardson number

KW - Semidiurnal tide

KW - Sodium lidar

KW - Static instability

UR - http://www.scopus.com/inward/record.url?scp=85148472190&partnerID=8YFLogxK

U2 - 10.1186/s40623-023-01771-1

DO - 10.1186/s40623-023-01771-1

M3 - Article

AN - SCOPUS:85148472190

SN - 1343-8832

VL - 75

JO - Earth Planets and Space

JF - Earth Planets and Space

IS - 1

M1 - 22 (2023)

ER -