the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Troposphere – stratosphere integrated BrO profile retrieval over the central Pacific Ocean
Theodore K. Koenig
Francois Hendrick
Douglas Kinnison
Christopher F. Lee
Michel Van Roozendael
Rainer Volkamer
Abstract. Bromine is a reactive trace element in the atmosphere, that destroys ozone, oxidizes mercury, modifies oxidative capacity and affects the lifetime of climate-active gases (e.g., methane). About 75 % of tropospheric ozone and methane is destroyed in the tropics, primarily in the lower free troposphere, where bromine monoxide (BrO) radical measurements are generally scarce. The few available aircraft observations find BrO is variable, and measurements in different compartments of the atmosphere are not easily reconciled. While zenith-sky DOAS measurements provide long-term records of the stratospheric O3 and NO2 abundances, autonomous MAX-DOAS placed at remote mountaintop observatories (MT-DOAS) provides cost effective and maximally sensitive access to probe the lower free troposphere, a climate-relevant yet understudied region of the atmosphere.
Here we describe and evaluate an innovative full-atmosphere BrO and formaldehyde (HCHO) profile retrieval algorithm using MT-DOAS measurements at Mauna Loa Observatory (19.536° N; 155.577° W; 3401 m asl) during two case study days, characterized by the absence (26 Apr 2017, base case) and presence of a Rossby Wave breaking double tropopause (29 Apr 2017, RW-DT case) above Big Island, Hawaii. The full atmosphere retrieval is based on time-dependent optimal estimation, and simultaneously inverts 190+ individual BrO (and formaldehyde, HCHO) SCDs (slant column densities, SCD = dSCD + SCDRef) from solar stray light spectra measured in the zenith and off-axis geometries at high and low solar zenith angle (92º > SZA > 30º) to derive BrO concentration profiles with 7.5 degrees of freedom (DoF) from 1.9 to 35 km altitude. Stratospheric BrO vertical columns are near identical on both days (VCD = (1.5 ± 0.2) ×1013 molec cm-2), and the stratospheric BrO profile peaks at a lower altitude during the Rossby wave breaking event (1.6 – 2.0 DoFs). Tropospheric BrO VCDs increase from (0.70 ± 0.14) ×1013 molec cm-2 (base case) to (1.00 ± 0.14) ×1013 molec cm-2 (RW-DT), owing to a tropospheric BrO profile re-distribution characterized by a three-fold increase in BrO located in the upper troposphere (1.7 – 1.9 DoF). BrO is found to be more variable in the lower free troposphere (0.2 pptv < BrO < 0.9 pptv) and characterized in three altitude layers (near, above, below) MLO with added time resolution (~3.8 DoF). The BrO mixing ratio at MLO increases from (0.23 ± 0.03) pptv (base case) to (0.46 ± 0.03) pptv BrO (RW-DT); while the maximum of (0.9 ± 0.1) pptv BrO is observed above MLO in the lower free troposphere in absence of the double tropopause.
We validate the retrieval using aircraft BrO profiles and in-situ HCHO measurements aboard the NSF/NCAR GV aircraft above MLO (11 Jan 2014) that establish BrO peaks around 2.4 pptv above 13 km in the UTLS during a similar RW-DT event (0.83 ×1013 molec cm-2 tropospheric BrO VCD above 2 km). The tropospheric BrO profile measured from MT-DOAS (RW-DT case) and the aircraft agree well (after averaging kernel smoothing). Furthermore, these tropospheric BrO profiles over the Central Pacific are found to closely resemble those over the Eastern Pacific Ocean (2–14 km); and contrast with the Western Pacific Ocean, where a C-shaped tropospheric BrO profile shape had been observed.
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Theodore K. Koenig et al.
Status: open (until 25 Dec 2023)
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RC1: 'Comment on egusphere-2023-2150', Anonymous Referee #1, 06 Dec 2023
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General Comments
The manuscript entitled „Troposphere – stratosphere integrated BrO profile retrieval over the central Pacific Ocean” by Koenig et al. presents a novel retrieval algorithm for the simultaneous determination of tropospheric and stratospheric trace gases and aerosols from MAX-DOAS measurements performed on mountain tops.
Knowledge on the composition of the atmosphere, in particular in the upper troposphere and stratosphere, is crucial for the understanding of the atmospheric chemistry and its impact on climate. MAX-DOAS measurements provide a simple and cost-effective way to retrieve information on the vertical distribution of atmospheric trace gases. The mountain-top based MAX-DOAS system presented here allows for gaining enhanced information on the UT/LS region. The authors describe novel and improved retrieval methods, and the subject of the manuscript fits well into the scope of AMT.
The level of agreement of modelled and measured diurnal variability of dSCDs is impressive, indicating that the retrieval is modelling the atmospheric radiative transfer realistically. However, I find it difficult to understand the principal approach of the so-called “Time-dependent retrieval”, and I feel that the respective section 2.5.3. requires substantial revision as detailed in the specific comments.
The abstract is too long and should, as an AMT contribution, focus more on the retrieval algorithm itself than on the chemistry of the UT/LS region, for which far too many details are provided.
Specific Comments
L13: The term “trace element” is not appropriate for bromine since it has an impact on atmospheric chemistry not only in its elemental form.
L76: It would be good if you would be more specific regarding the exploitation of the “sun motion” (i.e., increase in light path with increasing SZA).
L149: It is possible to fit certain parameters or state/measurement vector elements, but it not possible to fit “degrees of freedom”. Please specify what is fitted here.
L161 and thereafter: What do you mean with the term “principal program”? Are the RTMs not just programs?
L177: Can you give an estimate how large the errors are if the atmosphere below the instrument is not considered in the DISORT model? Can this simplification be justified?
Section 2.3.: Please explain why you use two different RTMs in a single retrieval algorithm. This is a quite unusual approach. McArtim is capable of modelling both tropospheric and stratospheric radiative transfer also during twilight, so it is not clear what the advantage of using DISORT is.
L195: It is not clear what you mean with “layering approach”.
Sections 2.5.1 and 3.3.3: Is there a specific reason why SCD_ref is not simply retrieved as part of the state vector in the optimal estimation algorithm, instead of using Langley plots as an extra step?
Section 2.5.3 requires substantial revision as it is not possible to understand what the actual approach is. What is the basic idea behind your approach? What is the difference between time-dependent and time-independent retrievals? The term “time-independent formulation” occurs in L291, but it is not explained anywhere what this means. What is the exact meaning of the mathematical objects in Equation 3, which of these are scalars, vectors or matrices, and what are their shapes/dimensions? Does the vector x contain profiles at a single time or are BrO profiles over a period of time which are retrieved simultaneously? What exactly is x_0 and how is it determined? Please specify in detail the individual components of the measurement vector and the state vector.
Eq. 4: It is stated that H represents a Jacobian, but H = K_0*x is not a Jacobian Matrix but a vector in measurement space.
L317: I suppose the “high concentrations” of BrO are expected in the FT. Please specify.
L354: Cross-sections do not have an optical density. Please rephrase.
L357: To what is the Aliwell fit window insensitive?
L363: Is a wavelength shift of 3 pm leading to any noticeable difference in the fit if the instrument has a spectral resolution of about 0.5 nm?
L376: Please explain why the O4 scaling factor should scale with lambda^4 like Rayleigh extinction. I do not see an immediate physical reason for this.
L382: Please explain what you mean with “intensity effects”. Could this be instrumental non-linearity? If you suspect that NO2 is affected by such effects, then why not other trace gases, in particular if they have lower optical density?
L395ff: Here it is not clear what you mean with the terms “component” and “signal”. Do they refer to the retrieved dSCDs or to the fit residuals? What exactly are replicate measurements? Do you mean subsequent measurements along the same line of sight?
L564: A “change” has no DoF.
L635: Here it would be good to cite Rodgers and Connor [2003].
L640: In what respect is the analysis limited by the RTM calculations? In terms of accuracy? Computational time?
L643: To my knowledge, McArtim already fulfils the required capabilities listed here – see Deutschmann et al. [2011].
Please add a “Code Availability” section stating the availability of the retrieval algorithm presented here.
Technical Corrections
L30: near -> nearly
L56: “BrOx adds radical species to oxidative capacity” does not make much sense. Suggestion: “BrOx increases the oxidative capacity”
L106: I guess you mean the azimuth angle when you talk about “primary viewing direction”?
L123: What do you mean with the dagger symbol as prefix for the elevation angles?
L175: Stratospheric aerosol WAS modelled…
L189: Tropospheric aerosol WAS assumed…
L190: Approximated by an approximation?
L194: Add “The retrieval of” to the beginning of the sentence
L393: The term “method-based anticorrelation” is not clear to me.
L404: The part of the sentence after the semicolon is without any context.
L409: I suggest to add that the additional HCHO absorption feature is at 330 nm.
L497: comparison -> difference
L506: “While it is clear the retrieval … can be further improved” is grammatically incorrect. Is a “that” missing?
L585: Explain abbreviation “KOA”.
References
- Deutschmann et al., “The Monte Carlo atmospheric radiative transfer model McArtim: Introduction and validation of Jacobians and 3D features,” J. Quant. Spec. Rad. Trans., vol. 112, pp. 1119–1137, 2011, doi: 10.1016/j.jqsrt.2010.12.009.
- D. Rodgers and B. J. Connor, “Intercomparison of remote sounding instruments,” J. Geophys. Res, vol. 108, no. D3, pp. 4116–4229, 2003, doi: 10.1029/2002JD002299.
Citation: https://doi.org/10.5194/egusphere-2023-2150-RC1
Theodore K. Koenig et al.
Theodore K. Koenig et al.
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