Resolving the mesospheric nighttime 4.3 µm emission puzzle: comparison of the CO<sub>2</sub>(<i>ν</i><sub>3</sub>) and OH(<i>ν</i>) emission models

Abstract

Abstract. In the 1970s, the mechanism of vibrational energy transfer from chemically produced OH(ν) in the nighttime mesosphere to the CO 2 (ν 3 ) vibration, OH(ν) ⇒ N 2 (ν) ⇒ CO 2 (ν 3 ), was proposed. In later studies it was shown that this "direct" mechanism for simulated nighttime 4.3 µm emissions of the mesosphere is not sufficient to explain space observations. In order to better simulate these observations, an additional enhancement is needed that would be equivalent to the production of 2.8-3 N 2 (1) molecules instead of one N 2 (1) molecule in each quenching reaction of OH(ν) + N 2 (0). Recently a new "indirect" channel of the OH(ν) energy transfer to N 2 (ν) vibrations, OH(ν) ⇒ O( 1 D) ⇒ N 2 (ν), was suggested and then confirmed in a laboratory experiment, where its rate for OH(ν = 9) + O( 3 P) was measured. We studied in detail the impact of the "direct" and "indirect" mechanisms on CO 2 (ν 3 ) and OH(ν) vibrational level populations and emissions. We also compared our calculations with (a) the SABER/TIMED nighttime 4.3 µm CO 2 and OH 1.6 and 2.0 µm limb radiances of the mesosphere-lower thermosphere (MLT) and (b) with ground-and space-based observations of OH(ν) densities in the nighttime mesosphere. We found that the new "indirect" channel provides a strong enhancement of the 4.3 µm CO 2 emission, which is comparable to that obtained with the "direct" mechanism alone but assuming an efficiency that is 3 times higher. The model based on the "indirect" channel also produces OH(ν) density distributions which are in good agreement with both SABER limb OH emission observations and ground and space measurements. This is, however, not true for the model which relies on the "direct" mechanism alone. This discrepancy is caused by the lack of an efficient redistribution of the OH(ν) energy from higher vibrational levels emitting at 2.0 µm to lower levels emitting at 1.6 µm. In contrast, the new "indirect" mechanism efficiently removes at least five quanta in each OH(ν ≥ 5) + O( 3 P) collision and provides the OH(ν) distributions which agree with both SABER limb OH emission observations and ground-and space-based OH(ν) density measurements. This analysis suggests that the important mechanism of the OH(ν) vibrational energy relaxation in the nighttime MLT, which was missing in the emission models of this atmospheric layer, has been finally identified.

Validation of SABER v2.0 Operational Temperature Data With Ground‐Based Lidars in the Mesosphere‐Lower Thermosphere Region (75–105 km)

“…Remsberg et al (2008) found that the uncertainties associated with the CO 2 VMR contributed one of the largest sources of systematic error in the non-LTE region, with uncertainty values of 1. Feofilov et al, 2012;Panka et al, 2017), and the uncertainties associated with CO 2 (ν 2 ) vibrational quanta exchange rate constant (k vv ). García-Comas et al (2008) demonstrated that the non-LTE region T k (z) errors vary with both latitude and season and were largest during the polar summer (compared to a midlatitude summer location).…”

Atomic Oxygen Retrieved From the SABER 2.0‐ and 1.6‐μm Radiances Using New First‐Principles Nighttime OH(v) Model

“…The model of Panka et al (2017) is the first one which accounts for the new vibrational relaxation pathway of OH(v) by collisions with O( 3 P) atoms…”

“…This effect is, however, much more prominent in the OH VERs for channel 9 (middle panel). Unlike the higher vibrational levels, the lower ones are quenched by O 2 at a much slower rate (see Table 1 of Panka et al, 2017) and, therefore, reaction (2) plays here a more important role.…”

Boundary of Nighttime Ozone Chemical Equilibrium in the Mesopause Region From SABER Data: Implications for Derivation of Atomic Oxygen and Atomic Hydrogen

“…In particular, Mlynczak et al (2018) changed the parameters of the SABER-2013 OH(v) model, which resulted in smaller nighttime O concentrations compared to SABER-2013, and hence a more realistic global annual mean energy budget of the MLT. Panka et al (2018) used the OH(v) model (Panka et al, 2017) for a novel algorithm which did not rely on the assumption of nighttime ozone equilibrium to derive nighttime O. This allowed the authors to eliminate the above-mentioned discrepancies between O distributions derived from SABER data and other satellite airglow observations.…”