the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Dec 2025
Characterisation of spectroscopic properties of DOAS instruments using high-resolution solar spectra
Abstract. The characterisation of spectroscopic properties of DOAS instruments is important for accurate trace gas retrievals. In this study, we investigate and extend existing methods for the determination of spectroscopic properties using high-resolution solar spectra (also known as Kurucz fit, KF, approaches). We apply these methods to long-term zenith sky DOAS measurements in Kiruna (northern Sweden). This unique data set allows to study the performance and precision of such fitting procedures under different environmental and observational conditions. Also, the effect of the change of the detector from a photodiode array to a modern CCD is investigated. One key finding of our study is that the so-called Ring effect (caused by rotational Raman scattering) leads to a systematic broadening (by typically about 10 %) of the width of the instrument spectral response function (ISRF) derived from a KF compared to the true ISRF derived from atomic line lamp measurements. Especially for measurements of trace gases located close to the ground this broadening can lead to errors of the trace gas results if a KF-derived ISRF is used for the preparation of trace gas reference spectra and Ring spectra. Here it is important that the strength of the Ring effect can strongly change due to clouds, in particular in the presence of optically thick clouds. Measurements in the presence of optically thick clouds should thus not be chosen for the application of the KF. Another specific finding for the Kiruna measurements (also relevant for other high latitude stations) is that the Ring effect changes systematically with season because of the changing surface albedo (caused by snow cover in the winter). From KF, different instrument properties can be obtained. We give specific recommendations for different KF variants for the determination of the ISRF, intensity offsets (e.g. caused by spectrograph straylight), or the wavelength dependence of the light throughput of the instrument. We also show that a strong wavelength dependence of the light throughput (e.g. caused by the Fabry–Pérot etalon effect) can lead to wrong trace gas results. This finding might also be relevant for other instruments affected by strong Fabry–Pérot etalon effects, or containing other optical elements with strong wavelength-dependent light throughputs. Finally, we introduce a method to correct such a wavelength-dependent light throughput using the results of a modified KF.
Competing interests: Steffen beirle, Ulrich Platt, and Thomas Wagner are members of the editorial board of Atmospheric Measurement Techniques
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-5878', Anonymous Referee #1, 02 Feb 2026
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RC2: 'Comment on egusphere-2025-5878', Anonymous Referee #2, 23 Feb 2026
General Comments
This manuscript evaluates spectroscopic properties of zenith-sky-viewing DOAS instruments by extending the Kurucz fit method using high-resolution solar spectra. The method is applied to 30 years of UV-visible zenith-sky spectra recorded at Kiruna, Sweden, to characterize the dependence of instrument properties (instrument spectral response function, intensity bias, light throughput) on different observing conditions, and to assess the effect of changing from a photodiode array to a CCD detector. The manuscript clearly states the primary findings and gives specific recommendations for applying the Kurucz fit. A major conclusions is that the Ring effect causes a systematic broadening of the width of the instrument spectral response function derived from the Kurucz fit compared to that derived from mercury lamp measurements. The strength of the Ring effect is found to change when optically thick clouds are present and to have a seasonal dependence due to the surface albedo. The manuscript also presents a method for correcting wavelength dependence of the light throughput (such as that caused by the Fabry–Pérot etalon effect) using the results of a modified Kurucz fit.
The work is clearly presented and will be of interest to those involved in UV-visible spectroscopy and DOAS measurements of atmospheric trace gases. I have only a few minor comments to add to those of Reviewer 1, and I recommend publication after both sets of comments are addressed.
Specific Comments
Page 7, line 170: Text refers to Figure A3 on page 35 as showing variations of the strength of the Ring effect due to the varying cloud cover, but the figure shows FWHM vs. RSP. It is not clear from the figure or caption how this is related to varying cloud cover – explain.
Page 9, lines 205-211 and Page 10, Table 1: Clarify why different fitting parameters are used for each of the BrO bands.
Page 12, paragraphs 1 and 2: Could correlation plots be added to strengthen the conclusions regarding the various hypotheses?
Page 28, end of paragraph 2: Comment on relevance of these findings to MAX-DOAS scattered-light measurements.
Page 29, lines 588-591: The reasoning in this last paragraph seems circular (“it is recommended to monitor the instrument characteristics of a DOAS instrument … In this way … the instrument properties can be continuously monitored during routine operations”). Suggest rewriting this paragraph for a clearer final message.
Technical Corrections
I noted many of the same typographical corrections as Reviewer 1 (ist, Mio, prepared, teh, charateristics, spectromter, etc.) so will not repeat them here.
Check the manuscript for correct use of hyphens in compound adjectives before nouns, e.g., for zenith-sky, clear-sky long-term, high-resolution, wavelength-dependent etc.
Many sentences could benefit from the use of commas to separate clauses.
Wikipedia is cited twice as a reference (for the length of polar day and night, and for snow cover, at Kiruna). Both should be replaced by references to primary sources.Check capitalization of sect./section --> Sect./Section, eq./equation --> Eq./Equation, appendix --> Appendix. Also follow AMT guidelines on when to abbreviate section, equation, and figure.
Numbers could be written as words when not referring to specific values.
Add punctuation after equations.
Page 2, line 32: define DOAS
Page 2, line 54: Here and throughout - why use “sub window” (sub-window)? No windows have been defined, so why not “fitting window”?
Page 4, lines 92-93, 102, and in legend of Figure 1a: capitalize Swedish Institute for Space Physics
Page 5, Equation 1: define all terms in this equation
Page 9, line 195: Fig. A4 (not 4A)
Page 9, line 208: define FRS on first use (it’s defined on page 12, line 237)
Page 10, caption and first row: change Alliwell to Aliwell
Page 12, line 252: there are no “black dots” in Figure 5 - fix
Page 20, line 399: change migh to might
Page 27, line 519: change monotonous to monotonic
Page 33, line 698: change self-built to custom-built
Page 33, line 702: change photo diode to photodiode
Page 33, line 707: Is the integration 6 minutes at all SZA? Wouldn’t noon spectra be saturated for such a long integration time?
Page 41, line 800, 805, 806, 811, 825: broad band --> broadband
Citation: https://doi.org/10.5194/egusphere-2025-5878-RC2 -
RC3: 'Comment on egusphere-2025-5878', Anonymous Referee #3, 24 Feb 2026
Wagner et al. describe methods for characterization of instrumental effects on DOAS retrievals. The analysis uses a novel long-term record (30 years) of spectra from the Kiruna station in northern Sweden. The manuscript is well written and describes important instrumental effects that should be considered for retrievals of trace gas slant columns from ultraviolet absorption measurements. The manuscript fits well into AMT and I would recommend publication. Below are some general comments on the novelty of key findings, a few topics that the authors should consider, and some small technical fixes.
The manuscript shows that:
The Ring effect (atmospheric Raman scattering filling intensity dips in solar spectra) broadens the instrument spectral response function (ISRF) as measured by fitting of observed solar spectra.
As the Ring effect is enhanced by clouds, the authors suggest cloudy spectra should not be used to determine the instrument spectral response function (ISRF). Authors also show that there isa. seasonal variation due to albedo, which enhances ring effect in winter at this high latitude location.
Interestingly, for retrievals of trace gas slant columns of primarily stratospheric absorbers, such as BrO (at this inland location), convolution with the Ring-effect-broadened ISRF appears better because the Raman scattering happens after the absorption by BrO in the stratosphere. However, retrievals lower in the atmosphere may be affected.
The use of convoluted high resolution solar spectra as "Frauenhofer" reference spectra (FRS) is used to develop methods to determine instrumental light throughput and its wavelength dependence, which can improve trace gas retrievals.
The authors make good suggestions for how future researchers can use this information, assisting the DOAS community in consideration of bandwidth effects in DOAS retrievals.
Broader points for consideration:
Lines 326-328. In this section, the authors argume that the filling in of the spectral dips by Raman scattering happens after trace gas absorption in the stratosphere and before detection, therefore, the appropriate ISRF is the one including the added width from Raman scattering. This is reasonable, but one point of evidence is that the retrieved BrO summertime values are "unrealistically low". Can there be a citation or more explanation of why the higher summertime BrO values should be accepted? Also in this section it was not clear if single values of the FWHM used for the full year in the Figure A6 analysis. Can the authors improve clarity on how the ISRF is used in this analysis?
Line 341. The authors say "varying ISRF gives the more exact results". Do they mean more "accurate" (closer to truth) or more "precise" (smaller variability)?
Line 393. The first sentence seems to describe the RSP, but it is not clear. Can "the values" be more clearly defined in this sentence?
About line 515, it says that the nonlinearity from allowing a shift is the cause of errors in the BrO retrieval. Does giving some constraint on the shift suppress this effect? Is the variation in the dSCD correlated to the fitted shift?
Typographical errors:
Line 61. Replace "ist" with "is"
Line 87. I'd say "located within the polar vortex"
p9, line 189. FWHM starts to increase after 2023 -- why is this?
Line 207. Has a typo, which should say "On that day of the year..."
Line 208. Define FRS.
Line 252. I think it should say "a similar monotonic increase of..."
Line 279. Doesn't the RSP vary with wavelength? The figure cited uses 340nm RSP, which should probably be mentioned. Possibly what matters is weaker wavelength dependence of the Raman / Rayliegh ratio. Can the authors comment?
Table 2 should mention the unit (nm).
Figure A6 says "with Raman" and "without Raman", but I think "without" is Raman removed, which is a bit different because the Raman was calculated and removal might not be perfectly correct. The x axis should also probably be "date" rather than "time", possibly specifying dd.mm.yy
Line 399. The word "might" has a missing "t".
Line 519. Should say "which is monotonic with wavelength..."
Citation: https://doi.org/10.5194/egusphere-2025-5878-RC3
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- 1
The paper "Characterisation of spectroscopic properties of DOAS instruments using high-resolution solar spectra” by Thomas Wagner et al., presents a comprehensive investigation of spectroscopic properties of DOAS instruments using a Kurucz-fit approach applied to a long-term zenith-sky dataset from Kiruna, Sweden, spanning 30 years. The study investigates the impact of a detector change from a photodiode array to a CCD, demonstrates that the Ring effect leads to a systematic broadening of the retrieved ISRF, with a strong dependence on cloud conditions and seasonal changes in surface albedo. The authors provide also recommendations for the determination of the ISRF, intensity offsets and the wavelength dependence of the light throughput of the instrument. Continuous monitoring of the instrument properties is very important, particularly for long-term trend analyses, where instrumental effects can otherwise introduce biases.
The paper is well written, clearly structured and easy to follow, and its scientific content fits the scope of AMT. Below are my review, comments and remarks.
General comments:
(1) The authors state that the spectrometer of the instrument is maintained at 30±0.1°C (P.33, L.700). Nevertheless, could small temperature instabilities still contribute, at least partly, to the observed variability of retrieved instrumental parameters such as the FWHM? While the manuscript suggests that the dominant seasonal variability is driven by the Ring effect, an investigation of the diurnal variability of the retrieved instrument parameters during clear-sky days might help to assess the magnitude of (if any) remaining temperature-related contributions.
(2) Can the authors comment to what extent their main conclusions and recommendations apply to lower-latitude sites with weaker but still variable surface albedo and to other viewing geometries (e.g. MAX-DOAS)?
(3) In an ideal spectrometer the spectral line shape is determined by the grating, slit, and optics, while the detector merely samples the spectrum. The authors demonstrate that the older PDA detector is affected by the Fabry–Pérot etalon effect, which alters the sampled spectrum and influences the effective ISRF. Is this the only detector-related parameter that is different between the PDA and CCD sensor used in the study that may affect the ISRF?
(4) The authors conclude that, in order to obtain reasonable and spectrally consistent results of the ISRF FWHM, neither an intensity offset nor a Ring spectrum should be included in the KF. I think the authors should comment on whether this is expected to be an instrument-dependent conclusion and/or and if the same behavior is expected for different spectral regions (e.g. in the visible)
Specific comments:
P.3, L.71: The Fabry–Pérot etalon effect is first introduced at this point. While a short description of the effect is given in Sect. 4.2 (L.411-412), I think such a description is more appropriate here.
P.4, Fig. 1: What do IRF 1 and IRF 2 represent? The small hut on the roof and the room inside the institute, respectively?
P.5, L.117-120: Can the authors comment on how the KF performs at lower SZAs? Are similar results expected?
P.5, L.137-138: Is an ozone absorption cross section included in the fit as stated in L.110? Please clarify
P.7, L.154-157: Can the authors comment on why doesn’t the inclusion of a Ring spectrum and/or of an intensity offset improve the results, especially in the UV range? Is this an instrument-dependent observation?
P.8, Fig. 3b: Are there any missing data in panel b) between 2003 and 2007? Or is this due to a visualization reason?
P.13, Fig. 5: The simulated RSP (panel a) should either become differential RSP, relative to 80 deg. SZA, or for the measured RSPs (panels b and c) the ylabels should be dRSP
P. 20, L.309-400: Are there any lamp measurements to confirm the increase of the FWHM?
Technical corrections:
P.3, L.61: “ist” -> “is”
P.4, L.104: “ERS” -> “ESR”
P.4, L.109: “software QDOAS” -> “QDOAS software”
P.6, L.149: “Finally, also the effect…”. -> “Finally, the effect…”
P.7, L.160: “Mio spectra” -> “million spectra”
P.8, Fig. 3 caption: Color assignments are wrong. They should probably be magenta, cyan, orange and black. Please revise. Same applies for Fig. 14 and Fig. A4
P.9, L.206: “prpared” -> “prepared”
P.9, L.207: “teh” -> “the”
P.9, L.216-217: “According to Wikipedia (2025), snow cover generally lasts from late September to mid-May”. This sentence may be omitted since afterwards, the snow depth is given in Fig. 4a
P.10, Table 1 caption: “Also shown are the settings from Alliwell et al., (2002)” -> “The settings from Alliwell et al., (2002) are also shown/included”
P.11, Fig. 4: The x label names (month names) should be given in English. Same applies for Fig. 13. Also in panel d, the marker color of the legend for 341-348 nm is wrong
P.12, L.241: “Kuruzc” -> “Kurucz”
P.12, L.252: “…are shown (black dots)” -> “filled markers”?
P.12, L.253: “Fig, 5a” -> “Fig. 5a”
P.12, L.255 “(blue dots)” -> “(small dots/markers)”?
P.15, Fig. 7: A ylabel should be given
P.15, Fig. 7 caption and in all other places: “ISFR” -> “ISRF”
P.16, L.311-312: “the better choice” -> “the best choice” or “a better choice”
P.16, L.315: the word “however” is not necessary
P.16, Table 2 caption and in all other places: “super Gaussian” -> “super-Gaussian”
P. 20, L.408 “charateristics” -> “characteristics”
P. 21, L. 437: “Appendix 3” -> “Appendix A3”
P. 33, L.698 and 700: “spectromter” -> “spectrometer”
P. 33, Fig. A1 caption: Either include a) and b) texts in the two panels or replace with “left”-“right”. Also replace “the visible spectrometer” with “the spectrometer operating in the visible range” or something similar.
P. 41, L.797: “of scattered” is a duplicate