the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Total Carbon Column Observing Network's GGG2020 Data Version
Joshua L. Laughner
Geoffrey C. Toon
Joseph Mendonca
Christof Petri
Sébastien Roche
Debra Wunch
Jean-Francois Blavier
David W. T. Griffith
Pauli Heikkinen
Ralph F. Keeling
Matthäus Kiel
Rigel Kivi
Coleen M. Roehl
Britton B. Stephens
Bianca C. Baier
Huilin Chen
Yonghoon Choi
Nicholas M. Deutscher
Joshua P. DiGangi
Jochen Gross
Benedikt Herkommer
Pascal Jeseck
Thomas Laemmel
Erin McGee
Kathryn McKain
John Miller
Isamu Morino
Justus Notholt
Hirofumi Ohyama
David F. Pollard
Markus Rettinger
Haris Riris
Constantina Rousogenous
Mahesh Kumar Sha
Kei Shiomi
Kimberly Strong
Ralf Sussmann
Voltaire A. Velazco
Steven C. Wofsy
Minquiang Zhou
Paul O. Wennberg
Abstract. The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs) beginning in 2004 from over 30 current or past measurement sites around the world, using solar absorption spectroscopy in the near infrared region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions as well as to validate and improve observations made from spacebased sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near IR solar spectra and the associated data product. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to: converting the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc airmass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements.
All TCCON data are available through tccondata.org and hosted on CaltechDATA (data.caltech.edu). Each TCCON site has a unique DOI for its data record. An archive of all sites’ data is also available with the DOI 10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than one year after acquisition. Full details of data locations are provided in the data availability section.
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Joshua L. Laughner et al.
Status: open (until 19 Oct 2023)
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RC1: 'Comment on essd-2023-331', Denis Jouglet, 23 Sep 2023
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Review of the preprint essd-2023-331
Title : The Total Carbon Column Observing Network’s GGG2020 Data Version
Authors : J. Laughner et al.
General comments
I read this preprint with much interest. The TCCON network has been providing unique data set for several years, with important impacts on atmospheric composition, atmospheric-surface exchange knowledge, satellite measurement validation and spectroscopy improvements. The required level of accuracy for the TCCON products is very challenging, with permanent improvements in the product processing. Such a complete description is therefore very important for traceability and deserves peer-reviewed publication.
This paper very well describes the huge work done by the TCCON team to improve its data processing since the last GGG2014 version. The authors demonstrate that they fully manage their complete measurement chain (interferogram processing, prior, spectroscopy, calibration, etc.). Most part of the measurement chain have been updated and can be considered at the state of the art. The authors have been able to include new uncertainty sources (e.g. the O2 volume mixing ratio depletion with time). A large effort has been done to give an exhaustive enumeration and description of the changes with respect to GGG2014.
The improvement of the forward model was done on solid physical basis. Besides, a large part of the processing consists in empirical corrections. The scientific choices of them could be discussed because they mean that some effects are not fully understood, and raise some doubts on the absolute and inter-station accuracy. These choices are however pragmatic and can be considered as acceptable since they are well documented, rigorous, validated and still under improvement. Moreover they can be considered as a pure calibration, as it is done for many other physical sensors, given that the other properties of the sensor (e.g linearity) are also demonstrated. I will raise some questions about the scientific content of this paper (see section Specific science comments below) but they do not require major revisions. Nethertheless this paper uses assumptions made in Wunch et al. 2015, which is a technical note, not a peer-reviewed paper. Such assumptions should therefore be questioned here.
However, I think the main weakness of this paper is its lack of clarity:
- this paper is not self-sufficient, since many rationales can only be found in previous papers: Wunch et al. 2010, 2011 and 2015. I think that scientists not familiar with the data cannot understand this paper on its own. I had to go back and forth to these papers. This would at least require systematic references to these papers (probably including the section, figure or table number), and in most cases a quick reminder (for example in a more detailed introduction).
- some assumptions made in these previous works are not fully described in these papers. In some cases, I was even not able to find the answer (see examples below).
- the paper is very long. I think that all parts deserve publication, but it could be split or rearranged if possible (mostly the uncertainty budget).
I will suggest revisions in the Suggested clarity improvements section hereafter.
As a conclusion, I fully support the publication of this paper with minor revisions for the science content, and substantial revisions for the self-consistency (processing description, rationales and referencing).
Specific science comments
Section 1 - Introduction
- l 40: did you think of permanently removing channels in the center lines that become saturated at large SZA, so as to homogenize the biases along the SZA?
- l 48 : the assumption of “consistent across sites” seems to be in contradiction with Wunch et al 2011 appendix A.a (0.2ppm).
Even if instrument are perfectly consistent, their different environments (boreal vs tropics) could translate in apparent inconsistencies.
- l 58: be careful that the refraction effect may differ in the O2 and the other gas windows.
Section 2
- l 85 : I have a question a bit beyond the scope of this paper, but I did not get the answer in previous papers. What is exactly your definition of AK? In a bayesian framework, AK are usually defined as information coming from the measurement with respect to the prior. According to Wunch et al 2010 the retrieval is least square fitting of a scaling factor of an a priori profile, without an explicit value of any prior of this scaling factor and associated uncertainty.
Section 3
- Large works have been done for improving spectroscopy, but no estimation of the gains on Xgas accuracy is given. Following section 7.1, they seem not to prevent the ACDF empirical correction. Can you provide an estimation?
- section 3.3: The O2 column is estimated from the 1.27µm band (always this band?). The O2 spectroscopic parameters are optimized so that Xluft, which is the ratio of O2 column from spectroscopy to O2 column from local pressure measurement, is close to 1 with low variance. Only the O2 spectroscopic parameters are tuned, which means that the surface pressure measurement is assumed to be the truth. Therefore, why using the O2 band and not directly the surface pressure measurement for the O2 column estimation?
- section 3.3: you choose to change some spectroscopic coefficients from your empirical observations. This is fully understandable. Did you have any discussion about that with spectrocopists? Are your changes inside the uncertainties given by spectroscopists?
- l.173: You choose to use only one value, T700, but the temperature vertical profile may be heterogeneous, in particular in the boundary layer. Do you not think that this approximation could be source of error ?
- fig 2: In panel (b) a slope can still be observed.
Section 4
- Do you not think that cross-sections computed for interpolated met profile for each hour of a day would provide an improvement in the retrieval?
Section 5
- l.242: Does detector saturation often happen? Why do you not adjust the gains to the maximum possible intensity of the place? This is quite deterministic, depending mostly on AOD (not strongly on SZAs in the SWIR when AOD is low and SZA not at extreme values).
- l.243: In such saturation cases, only the very low frequencies are lost. These frequencies are mostly retrieved by the continuum fitting and should not bring information on gases. Do you think that gas information is lost in such configuration?
The exception could be the Collision Induced Absorption (CIA), in particular in the 1.27µm O2 band.
Section 6
- Is there no interference between the instrument continuum fitting and the O2 1.27µm CIA when using polynomial orders greater than 2? The CIA brings much information on O2 amount.
Section 7
- Section 7.1: can you confirm that the new ADCF are computed on the Xgas benefiting from the O2 spectroscopic improvements of section 3.3?
- l.395: you consider the temperature dependence of the ADCF as “spurious”. I think this a hypothesis (like symmetry of Xgas with respect to noon in equation (5)) that requires to be identified as is. Can natural phenomena not also be responsible for such trends? Probably seeing this effect on some but not all windows of a trace gas could enforce the spurious hypothesis.
- In section 3.3 you update the O2 spectroscopic coefficients, using O2 from the pressure sensor as the truth to fit. Here in section 7.1, why do you not do the same optimization exercise for the spectroscopic coefficients of trace gases, rather than a posteriori empirical correction? This would require an external truth which could be the in situ measurements of section 7.3.
L.406 mentions this plan for temperature dependence but could be enlarged to SZA dependence.
- Section 7.1.1: you remove the windows that are the more affected by the temperature dependence. What is your threshold for the decision of correcting or removing?
- Section 7.3: I would like to understand the differing results of GGG2014 and GGG2020. In l.455, what are the differences between the in situ dataset used for GGG2014 and that for GGG2020? Do you expect changes / improvements in your AICF estimation with the GGG2020 dataset? Larger variety of in situ instrument to vary the potential biases; larger range in weather conditions to disangle trends?
What is the size of the GGG2020 in situ data set? And thus the number of elements in fig 11?
OK this is answered in table 2, but should be given in plain text.
- The appendix C6 is very important for this paper. It would be useful to give orders of magnitudes of the several sources of uncertainties (partially given in table 3).
- Appendix C6 l.1213: Why do you take twice the std and not the std itself?
- l.518: I agree the presentation of fig11 is better than the older presentation (fig5 in Wunch et al 2010, fig.8 in Wunch et al. 2015). Please precise that the in situ ratio of the fig11 is equivalent to the inverse of the slope of the best fit of older papers.
- l.524: Here for CO2 the ratio is ~1.01%, whereas in Wunch et al. 2010 fig5 and in Wunch et al. 2015 fig8 it was ~1.1% (1/0.989). Can we conclude that the updates of the GFIT processing and the new ADCF described in this paper have provided such a ~10% improvement? If so, please emphasize it. If not, please explain why (the values are comparable since the data set are different).
- l.627: I think “small” is a bit under-evaluated, since for 420ppm the order of magnitude is the same as the one of the new XCO2 scale.
- As already mentioned in my “general comments”, this section is very interesting in terms of metrology. I would interpret section 7.1 as a correction of intrinsic quality of the detector (removing all artifacts regardless the conditions), and section 7.3 as the absolute calibration of the sensor (more precisely fit to WMO standard).
In previous papers, only airmass dependencies were corrected. But now we can see that the list of potential dependencies for intrinsic quality is larger:
- ADCF in section 7.1
- Atmospheric temperature dependency in section 7.1
- Impact of Xgas. The classical Xgas(TCCON) = f(Xgas(in situ)) (like fig.8 in Wunch et al. 2015) have been discarded in this paper (section 7.3), this implicitly mean that TCCON is linear with Xgas
- Impact of Xluft as seen by section 7.3 fig.11 (l.555 mentions that it will be a future update)
Maybe the paper should be more explicit about this “metrological” process.
As a consequence, and depending on the size of the section 7.3 data set, I think other dependencies could be looked for (humidity, AOD, altitude, etc.).
Section 8
- l.758: it is written that surface pressure measurement is used for calculating the total column of air, whereas previously it was said that the O2 absorption band is used for that purpose, this is contradiction.
- l.784: do you not think that after the works done in section 7.1, it could be possible to add the spectroscopic errors as an uncertainty source?
- l.784: It would be interesting to get an inter-instrument budget beside the single instrument budget. This would be very useful since one of the use of the network is to analysis spatial gradients. For example, error in the retrieval like the choice of the prior will be partially common to all instruments (partially because it may depend on latitude). Some errors (pointing error, FOV error) will be different from an instrument to another.
- l.868: the classical way would be to use the standard deviation, please explain why you use the median absolute deviation here (robustness to outliers?)
- l.878: In your sensitivity study (first part of section 8), you did not include the radiometric noise, which would be the main random error source. Most sources you considered should be quite constant over a day, so the assumption of reduce sources of random error sounds good to me. Be careful however that some sources of your sensitivity study could be slowly variable and therefore mostly seen in the mean bias, not in the median absolute deviation.
- table 3 and l.883: In “Mean abs. dev.” there is the contribution of the instrument, of the in situ measurement and of the comparison between both. Do you not think you should compare “Mean abs. dev.” with the quadratic summation of “Error budget” and “Epsilon_insitu”, rather than “Mean abs. dev.” with “error budget”?
Suggested clarity improvements
Section 1 - Introduction
- This introduction should be expanded, and divided into several sub-sections:
- It should recall the main uses of the TCCON network (as given in the abstract).
- It should explain that the scope of this paper is to describe the major changes from GGG2014 to GGG2020, justify why so hard work has undertaken. The expected accuracy for GGG2020 and the current performance of GGG2014 would be the best rationale.
- Introduction should also reference to Wunch et al 2011 and 2010, since the major parts of the algorithm are described in the 2011 paper.
- I think the complete window definition should be recalled in a table (or at least referenced) in introduction or in appendix. This will ease the comprehension of section 2 by newcomers (useful also for l126), and also give the current status.
- Introduction should recall the main steps of the retrieval (Bayesian approach or not?), including the cross-sections computation and the AK definition, so as to make the paper more self-consistent.
- L 75: maybe the introduction should also mention the systematic quality check done by the central facility? Does it include the filterings listed in section 7.3?
- Description of the new merge of several windows of line 30 is redundant with section 7.2 and therefore could not be mentioned in introduction. I was not able to find the way several windows were merged in previous papers.
- It is not clear in sections 1, 7.1 and 7.2 whether the ADCF correction and the window merging is performed on column densities or on column average dry mole fraction (l.52). Please clarify.
- Please precise that Vgas and VO2 are column densities, and give the physical unit.
- l 45: can you give a reference for the 0.25%?
- The “scaling factor” or “scaling correction” could already be named AICF, and the “empirical airmass-dependent correction” ADCF.
Section 2
- People knowing the CO2 spectroscopy could wonder why the weak window at 6536cm-1 is not mentioned, maybe you can refer to section 7.1.1 l.415 which brings the explanation. Same for the 4905cm-1 strong CO2 band.
- To what the “l” of “lCO2” refers to? In the OCO-2 mission, such band is called sCO2, and the ~6300cm-1 bands to wCO2, which is confusing here.
Maybe the “CO2 window centered at 6220 cm−1” (l.119), which is the first standard window, should be given a short name as it the case for sCO2 and lCO2?
Section 3
- For clarity, I think a chapter named “Improvement of the forward model and the retrieval” should be created to include sections 3, 4, 5 and 6. The following sort would be more obvious : 5, 4, 3, 6.
- L 114 : give a reference for “Numerous spectroscopic studies”?
- L149 : Xluft is an important notion, but new and never mathematically defined (later it is said “similar to Xair”). Please give the mathematical formula of Xluft.
Section 4
- Please recall (in introduction?) that the absorption cross-sections are pre-computed, using the meteorological profiles. Despite the 3-hourly new product, can you confirm in the plain text that only one profile per day is used?
Section 5
- section 5.2: I cannot catch the improvement of GGG2020 with respect to 2014 in this section.
- section 5.3: I was not able to find in literature (Wunch et al. 2011, 2015) that the TCCON interferometer is single—sided. Please mention it (introduction?), and provide the length of the short arm (as well as that of the long arm).
- l 309: please explain why it is “more efficient” : is it for a better SNR?
Section 6
- L 312: “spectral response of the instrument” is ambiguous, may be confused with ILS. I understand you are talking about the instrumental ”continuum”.
- L 320: “the discrete Legendre polynomials” is not mentioned in Wunch et al 2015. Do you confirm it? Why Legendre polynomials and not classical polynomials?
Please give the orders used per window (or at least their maximum).
Section 7
- Section 7.1: sub-sections would be welcome
- I think that equations (3), (4) and (5) cannot be understood without an explicit reference to Wunch et al 2011 appendix A.e.i (l356 mentions “like GGG2014” but Wunch et al 2015 does not mention it). Please refer to it. Please recall that f is a model for the observed Xgaz diurnal variation, making the important assumption that any symmetrical Xgaz variation around noon is not expected to be true but an artifact.
- I think an illustration of XCO2=f(t,theta) with several examples would be welcome, and also to show the standard deviation that is aimed at being minimized.
- I note that despite Wunch et al 2011, the sin() function is replaced by a linear function, why?
- l.383: please precise how you get these uncertainties.
- l 395: As far as I understand by comparison with previous papers, this temperature dependence correction is new in GGG2020. Please emphasize it.
- l 399: The use of the theta notation for potential temperature is source of confusion since theta is use earlier for SZA. Maybe you should change it.
- l.402: please detail the exact operation: division by the ACDF at theta_mid=310K? linear correction requesting the knowledge of theta_mid?
- L.419: in this paper, as well as in previous papers, HCl was never mentioned as an atmospheric gas measured by TCCON (see table 3 of Wunch et al 2015), but only as for the gas cell for interferometer calibration. The mentioned windows should therefore be explained.
- Section 7.2: after reading the Wunch et al. 2015, 2011 and 2010, I was not able to find the way windows were merged in GGG2014 and older. I do not fully understand the iterative process described here. Please detail it.
- l 432: you mention the “retrieval error”, previous papers seems not to define it. I think it should be given in section 1.
- l.472: please give the formula of the FVSI index (or give a reference). Is it computed for a single scan duration? What is the duration of a single scan? (it can be mentioned in section 1)
l.481 also requires to mention the duration of a single TCCON duration, so as to understand whether 30 TCCON is a large part of a 2h window or not.
- l.495: I guess ai is the averaging kernel, please clarify it.
- l.514 and fig.11 legend: please explicitly precise that the uncertainty bars are given by appendix C6.
- l.564: can you tell which way was used for each dataset?
- l.582: for clarity reason, I would suggest to start a new sub-section dedicated to O2 decrease, as this is a different correction source (even if applied simultaneously with new XCO2 standard).
- l.634: It is not clear in this paragraph whether the new product includes the variable O2 variable fraction or not. The answer is given later in l.692, with some redundancy, therefore I would discard the l.634 paragraph.
Section 8
- This chapter is very important and must be kept. But it is a long part in an already long paper, and a bit different from the remaining of the paper which explains the updates of GGG2020. I would suggest several solutions:
- To place it in a dedicated companion paper. This can be merged with appendix B (which is small).
- Or (preferred) to move the text between l.704 and 782 in appendix B. This part is largely an update of similar works by Wunch et al. 2015 (section 8), 2011 (appendix B)
- Text between l.704 and 782 at least deserves its own sub-section
- Please refer to Wunch et al. 2011 and Wunch et al. 2015 for section 8.
In particular l.776 & 777 can refer to Wunch et al. 2015 for more details on ME.
- I would change the numeration of 8.x for x in {2,..,10} to 8.1.x.
- l.854: Please define this scale factors for HCl and how to use them to assess the ILS (or give a reference)
Section 9
- I think it would be more consistent to place this section at the beginning of document, either after 2 of after section 6.
Typing corrections
The paper is well written, and I did not detect typos.
- Section 6.1 has no 6.x follower
- Section 7.1.1 has no 7.1.x follower
- figures 8, 9, 11 and their font should be enlarged
- l.1595: the link seems to be dead.
Citation: https://doi.org/10.5194/essd-2023-331-RC1
Joshua L. Laughner et al.
Data sets
2020 TCCON Data Release Total Carbon Column Observing Network (TCCON) Team https://doi.org/10.14291/TCCON.GGG2020
Model code and software
TCCON/GGG – GGG2020 G. Toon https://doi.org/10.14291/tccon.ggg2020.stable.R0
Joshua L. Laughner et al.
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