Trends in the Airglow Temperatures in the MLT Region—Part 2: SABER Observations and Comparisons to Model Simulations

Tai-Yin Huang,Michael Vanyo

doi:10.3390/atmos12020167

Abstract

The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements at low latitudes from 89 km to 97 km were used to derive the F10.7 and Ap index trends, and the trends were compared to model simulations. The annual mean nonzonal (e.g., at the model simulation location at 18° N, 290° E) SABER temperature showed a good-to-moderate correlation with F10.7, with a trend of 4.5–5.3 K/100 SFU, and a moderate-to-weak correlation with the Ap index, with a trend of 0.1–0.3 K/nT. The annual mean zonal mean SABER temperature was found to be highly correlated with the F10.7, with a similar trend, and moderately correlated with the Ap index, with a trend in a similar range. The correlation with the Ap index was significantly improved with a slightly larger trend when the zonal mean temperature was fitted with a 1-year backward shift in the Ap index. The F10.7 (Ap index) trends in the simulated O2 and the O(1S) temperature were smaller (larger) than those in the annual mean nonzonal mean SABER temperature. The trends from the simulations were better compared to those in the annual mean zonal mean temperature. The comparisons were even better when compared to the trend results obtained from fitting with a backward shift in the Ap index.

Highlights

Several studies have used airglow intensity or airglow temperature measurements to find trends in temperature [1,2,3,4,5,6]
(3) The Ap index trends in Table 3 were ~30% larger than the values in Table 2 for all three altitudes and showed a much stronger correlation. These results indicate that annual mean zonal mean SABER temperature was highly correlated with Ap index when the Ap index was shifted 1 year backward
We should note that even without the shift in Ap index, the temperature alsTo d=e(m0.o29n6st±ra0t.e0d6)a×mAopd+er1a7t9e.3c4orrelation with A0p.78in66dex. Another thing to be noted is that such time lag was not seen in the model-simulated airglow tempW erahteunrews ebycoHmupaanregdatnhde Vtraenydore(2su02lt0s)f[r1o3m]. [T1h3]e tcoatuhsee rfeosrutlhtsefrtiommetdhelaynnoufaSlAmBeEaRn tzeomnpalermateuarneSrAesBpEoRnsteemtopgeeroamtuaregnweittihcoauctiavisthyi,fitfiint iAspreianld, eisxs, twilleunnoktendowthnatatnhde iFs1b0e.7yo(Andp tihnedescxo) ptreenodf sthweecruerlraerngtesrt(usdmya.lIletri)sihnoSpAeBdEtRhatteomupresrtautudryewatiltlhberOin2gatnhdisOto(1tSh)epaetatkenhteioignhotsf. tChoemscpieanritnifgicthcoemsimmuunlaittiyofnorrefsuurltthsetroitnhveersetisgualttsioonb.tained from the temperature fitted with a 1-year shift in the Ap index, we found that the Ap index trends in the annual mean zonal mean SABER temperature became larger and closer to the Ap index trends from the simulations at the O2 and O(1S) peak heights

Summary

Introduction

Several studies have used airglow intensity or airglow temperature measurements to find trends in temperature [1,2,3,4,5,6]. The recent simulation studies by the authors of [7,8] showed that airglow intensities of OH(8,3), O2 atmospheric band, and O(1S) Greenline in the Mesosphere and Lower Thermosphere (MLT) region responded to the influences of the CO2 increase and the F10.7 and Ap index variations In these studies, OH Chemistry Dynamics (OHCD) and Multiple-Airglow Chemistry Dynamics (MACD) airglow models [9,10,11,12] were used to simulate airglow response to the influences. In Part 1 of this series by the authors of [13], the OHCD and the MACD model were used to simulate airglow intensity-weighted temperatures of the aforementioned airglow under the influence of the CO2 increase and F10.7 and Ap index variations from 1960 to 2019 Their simulation results were in agreement with the findings from other studies, i.e., solar response in temperature still remains one of the major sources of variations.

SABER Data

Results

Conclusions