Validation of the MIPAS CO₂ volume mixing ratio in the mesosphere and lower thermosphere and comparison with WACCM simulations

Abstract

We present the validation of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) CO2 daytime concentration in the mesosphere and lower thermosphere by comparing with Atmospheric Chemistry Experiment (ACE) Fourier transform spectrometer and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) data. MIPAS shows a very good agreement with ACE below 100 km with differences of ∼5%. Above 100 km, MIPAS CO2 is generally lower than ACE with differences growing from ∼5% at 100 km to 20–40% near 110–120 km. Part of this disagreement can be explained by the lack of a nonlocal thermodynamic equilibrium correction in ACE. MIPAS also agrees very well (∼5%) with SABER below 100 km. At 90–105 km, MIPAS is generally smaller than SABER by 10–30% in the polar summers. At 100–120 km, MIPAS and SABER CO2 agree within ∼10% during equinox but, for solstice, MIPAS is larger by 10–25%, except near the polar summer. Whole Atmosphere Community Climate Model (WACCM) CO2 shows the major MIPAS features. At 75–100 km, the agreement is very good (∼5%), with maximum differences of ∼10%. At 95–115 km MIPAS CO2 is larger than WACCM by 20–30% in the winter hemisphere but smaller (20–40%) in the summer. Above 95–100 km WACCM generally overestimates MIPAS CO2 by about 20–80% except in the polar summer where underestimates it by 20–40%. MIPAS CO2 favors a large eddy diffusion below 100 km and suggests that the meridional circulation of the lower thermosphere is stronger than in WACCM. The three instruments and WACCM show a clear increase of CO2 with time, more markedly at 90–100 km.

On Long‐Term SABER CO2 Trends and Effects Due to Nonuniform Space and Time Sampling

“…There, it begins to decrease with increasing height due to molecular diffusive separation and photolysis (Garcia et al, 2014). The height where the CO 2 VMR departs from a well-mixed value (typically just above 80 km) varies in latitude and season as recently revealed by three independent satellite data sets (López-Puertas et al, 2017;Rezac, Jian, et al, 2015). The data combined with models indicate that both, the large-scale atmospheric circulation as well as external solar forcing, influence the upper atmospheric CO 2 spatiotemporal distribution.…”

“…However, this is not a significant issue in our analysis. Additional details and validation of the SD‐WACCM physics related to the MLT, especially in connection to CO 2 , can be found in Smith et al (), later validated with SABER data in Rezac, Jian, et al () and recently by MIPAS data in López‐Puertas et al ().…”

Analysis of 24 years of mesopause region OH rotational temperature observations at Davis, Antarctica – Part 1: long-term trends

“…Linear temperature trends were found to vary substantially depending on the time period chosen primarily due to the influence of the complicated temporal variation in ozone. Figure 3 of Lübken et al (2013) shows a monotonically increasing trend in CO 2 compared with a much more complicated temporal ozone variation (essentially constant until 1980, a rapid decrease from 1980 to 1995, followed by an increase since then). Trends in ozone vary as a function of both altitude and latitude, with positive trends dominating in the lower stratosphere and mesosphere (Laštovička, 2017).…”

“…Temperature trends are predominantly negative, and recent progress in understanding the magnitude of the cooling has arisen from confirmation and quantification of the role of ozone. Lübken et al (2013) present the results of trend studies in the mesosphere in the period 1961-2009 from the Leibniz-Institute Middle Atmosphere (LIMA) chemistry-transport model, which is driven with European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis below 40 km, and observed variations in CO 2 and O 3 . They find that CO 2 is the main driver of temperature change in the mesosphere, with O 3 contributing approximately one-third to the trend.…”

“…When analysing long-term trends, several authors (Lübken et al, 2013;Qian et al, 2019) emphasise the importance of specifying the length of the time period, as well as the beginning and end of the period, because trend drivers can be different for different periods (e.g. Yuan et al, 2019).…”