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Effect of 2009 major SSW event on the mesospheric CO2 cooling

T0 review · 4 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read During the 2009 sudden stratospheric warming, mesospheric carbon dioxide density and its infrared cooling moved in opposite directions, with temperature and atomic oxygen, not CO2 abundance, controlling the cooling.

desk verdict The paper's headline anti-correlation is likely a conversion artifact, not a real geophysical finding, but the case study is worth referee attention. read the letter →

arxiv 2412.01081 v1 pith:XC3L4BIN submitted 2024-12-02 physics.space-ph

Akash Kumar , MV Sunil Krishna , Alok K Ranjan This is my paper · ORCID
classification physics.space-ph
keywords suddenstratosphericwarmingmesosphereCO2infraredcooling15µmemissionatomicoxygenACE-FTSSABERmiddleatmospherecirculation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to establish that the 2009 major sudden stratospheric warming (SSW) reversed the usual relationship between carbon dioxide abundance and carbon dioxide infrared cooling in the polar mesosphere. Using satellite measurements near 85 km (0.003 hPa), the authors find that CO2 density increased during the warming peak and dropped during recovery, while CO2 15 µm radiative cooling moved the other way, giving a strong anti-correlation ($R = -0.865$). They argue that the cooling changes were driven mainly by temperature swings of about 20 K in either direction, followed by large atomic oxygen density changes, and that the CO2 density change itself was insignificant. If correct, this means short-term dynamical events can decouple CO2 cooling from CO2 concentration, which matters for interpreting satellite cooling records and upper-atmosphere energy budgets.

What carries the argument

The $\mathrm{CO_2}(0110)/\mathrm{CO_2}(0000)$ population ratio—the fraction of CO2 molecules in the first excited bending vibrational state that emits at 15 µm—carries the argument. The paper evaluates this ratio with a two-level collisional excitation model using rate coefficients $k_1$ for O2/N2 and $k_2$ for O taken from the non-LTE literature. During the SSW, mesospheric temperature and O density fall at peak warming and rise at recovery, and those changes lower and raise the population ratio even though CO2 density changes in the opposite direction; the population ratio tracks the observed cooling pattern. The same calculation is then used to isolate the separate contributions of temperature, O, and O2 changes, showing temperature first and O second.

What would settle it

Recompute the CO2 number-density anomaly at 0.003 hPa using ACE-FTS mixing ratios with an independent temperature–pressure profile (for example, from a reanalysis or a model run that does not assimilate SABER) and repeat the correlation with SABER cooling; if the correlation coefficient falls well below 0.865 in magnitude, the anti-correlation is an artifact of the shared temperature field. A second check is to rerun the population-ratio calculation with CO2 density held at pre-SSW values and see whether the temperature- and O-driven cooling pattern still reproduces the observed anomaly.

Watch

Extended reading notes

Core claim

During the 2008–2009 Arctic winter, a major SSW with an elevated stratopause reversed the residual mean meridional circulation over 60–70°N: upwelling during the main phase lifted CO2-rich air upward, increasing mesospheric CO2 density by roughly 10–12%, while downwelling during recovery brought CO2-poor air down, reducing density by about 15%. Despite the larger CO2 density, SABER observed roughly 20% weaker 15 µm cooling at 0.003 hPa during the warming peak, and despite the lower CO2 density, roughly 120% stronger cooling during recovery. The correlation analysis gives $R = -0.865$ between CO2 density and cooling, $R = 0.927$ with temperature, and $R = 0.905$ with atomic oxygen density. The paper concludes that the temperature decrease during upwelling and the temperature increase during downwelling, amplified by O density changes through collisional excitation of the CO2 ν2 mode, control the cooling, making CO2 abundance changes dynamically secondary.

Load-bearing premise

The paper converts ACE-FTS CO2 mixing ratios to density but does not state which temperature and pressure data it uses for that conversion; if those come from the same SABER 15-µm retrieval that defines the cooling, the density and cooling anomalies share a common source and the reported anti-correlation could be inflated.

Editorial extensions

If this is right

  • During a major SSW, mesospheric CO2 density is a poor proxy for CO2 infrared cooling on sub-seasonal timescales.
  • The roughly 20 K mesospheric cooling at the warming peak is the dominant driver of the reduced cooling, and the comparable warming during recovery drives the enhanced cooling.
  • Atomic oxygen variations ranging from about −97% to +500% act as a secondary control by changing the collisional excitation of CO2 into the emitting state.
  • The same qualitative anti-correlation appears in the specified-dynamics model output, suggesting the upwelling/downwelling mechanism is robust, not a single-satellite artifact.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • One testable extension is to check other major SSWs (for example, 2013 and 2018) with the same SABER and ACE-FTS datasets to see whether the anti-correlation is a generic SSW signature or unique to the 2009 elevated-stratopause event.
  • Because SABER temperature is retrieved from the same 15 µm emission that defines the cooling, the high temperature–cooling correlation is partly self-referential; an independent temperature dataset would strengthen the causal attribution.
  • The large O density enhancement during recovery implies SSW downwelling delivers atomic oxygen from the thermosphere into the mesosphere, which could affect ozone chemistry and nightglow emissions in addition to CO2 cooling.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. This manuscript studies the 2009 major sudden stratospheric warming (SSW) and its effect on mesospheric CO2 15 µm radiative cooling. Using SABER temperature, CO2 cooling, and O density; ACE-FTS CO2 volume mixing ratio (VMR) converted to number density; and SD-WACCM-X winds, O2, and CO2 fields, the authors report a strong anti-correlation (R = -0.865) between CO2 density and CO2 IR cooling at 0.003 hPa (~85 km) in the 60-70°N zonal mean during January-February 2009. They interpret this in terms of circulation-driven upwelling/downwelling: during the SSW main phase, reduced temperature and atomic oxygen depress CO2 IR cooling despite increased CO2 density, while the recovery phase shows enhanced cooling despite reduced CO2 density. The paper concludes that temperature changes dominate the CO2 IR cooling variability, followed by atomic oxygen, with the CO2 density change itself insignificant.

Significance. The science question is timely and relevant: short-term, event-driven variability in mesospheric CO2 15 µm cooling bears directly on the MLT energy budget and on interpretations of long-term upper-atmosphere contraction. The study combines multiple observational data sets (ACE-FTS, SABER) with a specified-dynamics model run, uses no fitted parameters, and adopts rate coefficients from prior literature. If the central anti-correlation and attribution survive scrutiny, the paper would be a useful observational case study of dynamical control of mesospheric CO2 cooling during an SSW. However, the headline result as presented is not yet trustworthy: the VMR-to-density conversion is underspecified, the printed CO2 densities are unphysical, and the temperature-cooling correlation is partly non-independent. These issues affect the quantitative claims in Figures 4, 6, and 7 and the attribution in Section 3.4.

major comments (4)
  1. [Section 2 and Figure 4a] The VMR-to-density conversion is not specified beyond a citation to Finlayson-Pitts and Pitts Jr (1999). The authors must state exactly which temperature and pressure fields are used. If SABER temperature is used at the fixed 0.003 hPa surface, then n_CO2 = VMR * P / (k_B T), so the density anomalies become a 1/T transform of the temperature anomalies. Since SABER temperature and SABER CO2 cooling are both retrieved from the same 15 µm radiance, an anti-correlation between this 1/T proxy and the cooling would arise even for a perfectly constant CO2 VMR. Please redo the conversion with an independent temperature field (e.g., ACE-FTS or WACCM-X) and state the fields explicitly.
  2. [Section 3.2 and Figure 4a] The printed CO2 density values, approximately 2.5-4.5 × 10^13 cm^-3 at 0.003 hPa (~85 km), are physically implausible. At ~200 K and 0.003 hPa the air number density is about 1.1 × 10^14 cm^-3, so a VMR of 370 ppm corresponds to about 4 × 10^10 cm^-3, not 10^13 cm^-3. This implies a conversion or unit error of roughly three orders of magnitude. Because Section 3.2 and Section 3.4 use these densities to compute percentage anomalies and the O/CO2 and O2/CO2 ratios, the quantitative results and the attribution are directly affected. The authors must correct the conversion and recompute Figures 3, 4, 6, and 7.
  3. [Section 3.4 and Figure 8] The attribution model is a simplified two-level collisional excitation formula based on reactions R1 and R2 only. It omits radiative absorption, spontaneous emission, and the non-LTE exchange terms that determine the actual 15 µm cooling rate. The decomposition of the cooling variability into temperature, O, and O2 contributions in Figure 8 is therefore not a demonstrated decomposition of the cooling rate itself. Please justify this simplified population-ratio model against a non-LTE cooling calculation, or explicitly reframe the attribution as qualitative rather than quantitative.
  4. [Section 3.2 and Figures 3-4] The correlation coefficients (-0.865, 0.927, 0.905) are quoted without confidence intervals, significance tests, or a statement of effective sample size. The daily-mean time series are strongly autocorrelated, so the number of independent samples is much smaller than the number of days. In addition, the R = 0.927 between SABER temperature and SABER CO2 cooling is not an independent check, because both quantities are derived from the same 15 µm broadband radiance. Please provide uncertainty estimates and clearly identify which correlations are physically independent.
minor comments (4)
  1. [Abstract] There are typographical and grammatical errors: 'mesosphere and lower thermospher' should be 'mesosphere and lower thermosphere', and 'such a dramatic events' should be 'such dramatic events'.
  2. [Figure 4] The axis labels use '#1013' and '#10-8' instead of proper superscript notation. They should be rendered as '×10^13 cm^-3' and '×10^-8 W m^-3' for clarity.
  3. [Section 3.2] The sentence defining anomalies, 'Δ CO2 = CO2 − CO2', uses the same symbol for the daily value and the pre-SSW mean. Please use an overbar or a distinct symbol for the mean value to avoid ambiguity.
  4. [Section 3.2] The text states that CO2 density increased during the SSW main phase and decreased during recovery, while Figure 3 shows cooling anomalies of opposite sign. A short table of phase-mean anomalies for CO2 density, temperature, O density, and CO2 IR cooling would make the anti-correlation easier to follow and would help the reader judge the magnitudes.

Circularity Check

2 steps flagged · score 5.0 of 10

The cooling-temperature correlation in Fig. 4b is partly self-referential because both quantities come from the same 15-µm retrieval, and the ACE-FTS CO2 density conversion in Section 2 uses unspecified T/P fields, so the headline anti-correlation may be partly constructed from the temperature field rather than from actual CO2 abundance changes.

  1. self definitional [Section 2 (Data and Methodology); Figure 4b]
    "The temperature data is retrieved from the CO 2 15 µm emission and is available from nearly 15 km to 110 km, whereas, the O density data is available from 80 km to 100 km in the SABER database. The CO 2 cooling data available between 30-140 km in the level 2B database has been used. Figure 4: ... SABER-derived CO 2 IR cooling and temperature (b) ... R = 0.927."

    Both SABER temperature and SABER CO2 15-µm cooling are derived from the same 15-µm CO2 emission channel. The R = 0.927 in Fig. 4b is therefore not an independent test of the claim that temperature controls the cooling; the two fields share a common radiance source by construction. The Section 4 conclusion that temperature is the major contributing factor is consequently partly built into the retrieval identity rather than being an independent empirical finding.

  2. other [Section 2 (Data and Methodology); Figure 4a]
    "The CO 2 mixing ratio in parts per million (ppm) derived from the ACE-FTS Level 2 version 4.1/ 4.2 dataset in the polar region (60 ◦ - 70 ◦ N) has also been converted to density (cm −3) as per the scheme described in Finlayson-Pitts and Pitts Jr (1999)."

    The standard conversion n_CO2 = VMR * P/(k_B T) requires temperature and pressure fields, but the paper does not state which fields are used. If SABER temperature, or any temperature field that covaries with SABER 15-µm cooling, was used, then at the fixed 0.003 hPa level the CO2 density anomaly is approximately -ΔT/T plus the VMR anomaly; the Fig. 4a anti-correlation (R = -0.865) would then be largely an ideal-gas transform of the same temperature signal already correlated with the cooling. The printed density values in Fig. 4a (2.5-4.5 × 10^13 cm^-3 at ~370 ppm, 0.003 hPa, ~200 K) are also about three orders of magnitude too large, indicating a conversion or unit inconsistency.

full rationale

The paper is an observational correlation study rather than a parameter-fitting derivation, and no circular self-citation chain is load-bearing: Kumar et al. (2024) is used only for SSW background, and the population-ratio rate coefficients are taken from the external literature (Lopez-Puertas & Taylor, 2001). The ACE-FTS CO2 VMR data and the WACCM-X simulation provide independent support for circulation-driven CO2 changes, so the central claim is not wholly forced. However, two built-in dependencies weaken the causal attribution. First, SABER temperature and SABER CO2 IR cooling are retrieved from the same 15-µm emission, making the Fig. 4b correlation partly self-referential. Second, the conversion of ACE-FTS VMR to density is described only by a textbook citation with no statement of the temperature and pressure fields; if SABER temperature was used, the anti-correlation in Fig. 4a would be partly constructed rather than physically independent. The implausible magnitude of the reported CO2 densities in Fig. 4a reinforces the concern that the conversion is not transparent. These issues do not prove the conclusion false, but they prevent the headline anti-correlation and the 'temperature controls cooling' attribution from being accepted as fully independent observational results.

Assumptions & free parameters 0 free parameters · 4 assumptions · 0 invented entities

The central claims rest on the accuracy and independence of the SABER and ACE-FTS retrievals, on the unspecified T/P conversion for CO2 density, and on a simplified two-level population-ratio model. No free parameters are fitted in this study; rate coefficients come from Lopez-Puertas and Taylor (2001). No new entities are introduced.

assumptions (4)
  • domain assumption SABER temperature and CO2 cooling are accurate retrievals from the 15 um emission, and can be treated as independent enough for the correlation analysis.
    Both quantities come from the same instrument and emission band (Section 2), so their strong correlation (R=0.927) is not fully independent evidence.
  • domain assumption The ACE-FTS CO2 VMR to number density conversion uses a temperature/pressure field that does not itself induce the anti-correlation.
    The paper does not state which T,P fields are used; if SABER T is used, density anomalies become a transform of temperature.
  • domain assumption The simplified two-level population-ratio model with O and O2 collisional excitation rates from Lopez-Puertas and Taylor (2001) captures the essential physics of CO2 15 um non-LTE emission.
    Figure 8 attributes cooling changes mainly to T and O based on this model, ignoring radiative excitation and full non-LTE transfer.
  • domain assumption Daily zonal means between 60-70N from sparse ACE-FTS occultation sampling are representative of the polar mesosphere.
    ACE-FTS provides limited profiles per day; no error bars or sampling statistics are given.

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Cite this review

Pith. "Pith review of Effect of 2009 major SSW event on the mesospheric CO2 cooling." pith.science (2026). https://pith.science/paper/XC3L4BIN

@misc{pith2026241201081,
  author       = {Pith},
  title        = {Pith review of: Effect of 2009 major SSW event on the mesospheric CO2 cooling},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XC3L4BIN}},
  note         = {Machine review of arXiv:2412.01081}
}
read the original abstract

Carbon dioxide (CO2), an important trace species that is gradually increasing in the atmosphere due to anthropogenic activities, causes enhanced warming in the lower atmosphere. The increased concentration of CO2 in the upper atmosphere results in enhanced radiative cooling rates leading to the contraction of the upper atmosphere. Due to its long lifetime and large vertical gradient, CO2 concentration is also influenced by large dynamic events. We report a startling case of variability in CO2 density and its infrared radiative cooling rates in the mesosphere and lower thermospher during a major sudden stratospheric warming (SSW) event. A counter-intuitive connection between CO2 density and resulting CO2 radiative cooling has been observed during the 2009 major SSW event. The behaviour of CO2 cooling rates during such a dramatic events draw attention to our current understanding of CO2 infrared cooling variation and its connection to changes in CO2 concentration. The significance of temperature and atomic oxygen variability in the observed cooling patterns despite changes in CO2 concentration, is also highlighted.

Figures

Figures reproduced from arXiv: 2412.01081 by the authors.

Figure 1
Figure 1. The geomagnetic indices, Kp (black) and ap (magenta) obtained from the OMNIWeb (a), and temperature (red starred line) and zonal-mean zonal wind (blue crossed line) at the defining latitude (60◦ ) and pressure level (10 hPa) derived from SABER and SD WACCM-X (b), respectively, during the January-February 2009. The vertical dashed line indicates the peak warming time over the polar stratosphere. time of peak warming.… view at source ↗
Figure 2
Figure 2. The ACE-FTS measured daily mean CO2 mixing ratio (ppm) in the middle atmo￾sphere (a), zonally averaged at the measurement latitudes between 60◦ and 70◦ N (b) during the January-February 2009. hemispheric SSW events, a model study indicated that the northern polar region reflects the most significant modifications in CO2 concentrations in the MLT (Orsolini et al., 2022). Therefore, CO2 variability is investigated in … view at source ↗
Figure 3
Figure 3. The anomalies in the CO2 density (upper panels) measured by ACE-FTS (a), and calculated from SD WACCM-X (b), and IR cooling by CO2 fundamental band at 15 µm (lower panels) observed by SABER (c), and calculated from SD WACCM-X (d), during the 2009 SSW. The red-dashed line indicate the altitude of peak CO2 cooling. The vertical dashed line indicates the peak warming time over the polar stratosphere. The anomalies have… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: The correlation between-SABER derived daily mean CO2 IR cooling and ACE-FTS￾derived CO2 density (a), SABER-derived CO2 IR cooling and temperature (b), and CO2 IR cooling and O density (c), zonally averaged between 60◦ -70◦ N at 0.003 hPa level, during the 2009 major SS…
Figure 5
Figure 5. Figure 5: Wintertime residual mean meridional circulation derived from SD WACCM-X, before SSW onset (a), during the peak warming period (b), and in the recovery phase (c) of the 2009 SSW event. density over and above the climatological values during the initial and recovery phas…
Figure 6
Figure 6. Figure 6: Variations in the ACE-FTS derived CO2 density (contour lines) and SD WACCM-X estimated O2 (colormap) density (a), SABER derived temperature (contour lines) and O density (colormap) (b), and CO2 radiative flux (c) using SABER measurements (black line) and WACCM￾X output…
Figure 7
Figure 7. Figure 7: The anomalies in the O/CO2 density ratio (a), O2/CO2 density ratio (b), population ratio due to collisional excitation by O (c), and O2 (d), respectively, between 60◦ -70◦ N, during the 2009 SSW event. The vertical dashed line indicates the peak warming time over the p…
Figure 8
Figure 8. Figure 8: Variation in CO2(011 0) to CO2(000 0) population ratio due to temperature, O and O2 change (a), due to only temperature change (b), due to only O density change (c), and due to only O2 density change (d), respectively, at 0.003 hPa (∼85 km) and 60◦ -70◦ N, during the 2…

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