the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Mar 2026
Atmospheric CO2 and CH4 measurements at Schauinsland station, Germany: A comparative study of diurnal and seasonal variations at 12 and 35 m intake height
Abstract. At the atmospheric monitoring station Schauinsland (Black Forest, Germany), high-precision long-term measurements of atmospheric CO2 and CH4 have been conducted since 1972 and 1991, respectively. An additional air intake at 35 m a.g.l. (above ground level) has been installed alongside the existing intake at 12 m a.g.l in September 2021. To ensure consistency and continuity of the historic CO2 and CH4 time series, a three-year comparison between the two intake heights has been carried out. This revealed systematic differences in CO2 mole fractions between the two levels: During summer daytime diurnal mean CO2 mole fractions at 35 m are up to 0.5 ppm higher, while night-time values are up to 1.1 ppm lower, compared to 12 m, resulting in smaller diurnal amplitudes at 35 m. Seasonal mean CO2 mole fractions are lowered by up to 0.36 ppm at 35 m relative to 12 m in summer, whereas no significant differences are observed in winter. The diurnal and seasonal mean CH4 mole fraction differences between the two intake heights are negligible. However, highly frequent CH4 spikes originating from nearby grazing cows, which are present only during the summer months, increase hourly mean mole fractions at 12 m by up to 38 ppb, while no significant influence is measured at 35 m. The REBS (Robust Extraction of the Baseline Signal) algorithm is applied to the minutely CH4 summer data at 12 m and proved to be an effective approach for identification of data affected by very local influences.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-849', Anonymous Referee #1, 02 Apr 2026
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RC2: 'Comment on egusphere-2026-849', Anonymous Referee #2, 01 Jun 2026
Review Großmann et al. “Atmospheric CO2 and CH4 measurements at Schauinsland station, Germany: A comparative study of diurnal and seasonal variations at 12 and 35 m intake height”
This paper describes and carefully analyses the comparison between measurements made at different heights over a period of several years. This is a really good study with relevance for interpretation of such data, especially with regard to their representation in atmospheric models in the context of inverse model applications. The paper is well-written, and fits well within the scope of AMT. However, a few issues listed below should be addressed before the paper can be recommended for publication.
General comments:
Calculation of mean values: It is unclear if the statistical calculations were made using the requirement that both instruments have data available. Non-overlapping data will cause the means to not be compatible. Further, for the daily mean calculation (L147) is there a requirement that the number of daytime and nighttime hours are similar? Otherwise the diurnal cycle might cause a larger error in the daily mean, if for example all available 12 hours are in the night.
Section 2.6, description of REBS method: In 2.6 gamma is described as „the standard deviation of data below the baseline curve“. This differs somewhat from the description in section 2.1 of Ruckstuhl et al. (2012). Is gamma estimated daily, annually, or for the full time series? Or is REBS applied to various sections of the time series (in Line 370 it seems so) such that various estimates for gamma exist? It also should be discussed how it is avoided that the diurnal and seasonal cycle in CH4 affects the estimation. My guess is that gamma is derived from negative residuals (obs. – background) rather than from the observations themselves, which would certainly reduce, if not remove the influence from diurnal/seasonal variations. It would also be interesting to know what the actual value of gamma was, especially in the context of the discussions in 3.5 and 3.6.
For better traceability of the application of the REBS method it would be good if the (probly simple) code could be shared.
Specific comments
L55: add a semicolon before “or CH4 spikes”, as this has nothing to do with manual spike removal. May be consider having a separate sentence for the Westerland example.
L56: “At Ispra station” -> “At the Ispra station”
L233-235: “peak around noontime” this is not obvious to me, please mention specifically where in Fig. 6 this can be seen
L274: That the solar radiation drives the photochemical sink is clear, but the solar impact on anthropogenic sources is not. May be reformulate.
L289-290: I suggest replacing “like” with “as”
L314: “renders” > “render”; “introduces“ > “introduce“
L332: In the figure title and caption June is mentioned, here the text refers to July -> please correct
L371: Was REBS not only applied once with a specific setting? This is unclear, as the outcome of the method for a specific data point does seem to depend on the temporal context, and thus on whether it was applied to the full time series once, or for segments.
L389 – 395: It would be interesting to see if the application of REBS also to 35 m affects the biases seen in Fig. 13. So if the same filter algorithm is used for both levels.
Citation: https://doi.org/10.5194/egusphere-2026-849-RC2 -
RC3: 'Comment on egusphere-2026-849', Anonymous Referee #3, 25 Jun 2026
The article “Atmospheric CO2 and CH4 measurements at Schauinsland station, Germany: A comparative study of diurnal and seasonal variations at 12 and 35 m intake height” by Großmann et al. investigates the comparability and representativeness of two inlet locations at the Schauinsland monitoring station with respect to atmospheric CO₂ and CH₄ measurements. As Schauinsland has one of the longest continuous CO₂ records worldwide, maintaining an uninterrupted and consistent time series is essential for understanding long-term greenhouse gas trends and variability.
The manuscript is well structured and provides a comprehensive analysis of the observations. Its findings provide valuable guidance for assessing data consistency and maintaining the quality of long-term greenhouse gas records, also for other monitoring stations facing similar challenges related to inlet changes and data continuity.
Overall, the manuscript presents a relevant and useful contribution to the field of atmospheric greenhouse gas monitoring. I recommend publication after minor revisions outlined below.
Specific comments:
Page 1, line 28 ff: It is unclear why only continental greenhouse gas monitoring stations are cited as constraints for estimating both land and ocean carbon fluxes. Given the importance of marine observations for constraining ocean carbon fluxes, please add marine and ocean-based stations or clarify why they are not mentioned.
Page 2, line 35 ff: Could you please provide references to the observational networks used? It would also be helpful to briefly discuss how comparable and compatible the measurements from the different networks are.
Page 2, line 41: Please refer to the “WMO/GAW” recommendations, as these compatibility targets are defined within the Global Atmosphere Watch (GAW) programme rather than by “WMO” alone.
Page 2, line 42 ff: The term “precision” may be misleading, as the ICOS targets cited above refer to network compatibility rather than measurement precision. Consider replacing “precision” with “compatibility” or “measurement consistency” to avoid confusion.
Page 2, line 62 ff: Please consider using “dry mole fraction” instead of “mole fraction” throughout the manuscript, unless humidity effects are explicitly included.
Page 3, line 83 ff, Fig. 1: For the further discussion, it would be helpful if the authors could include in Figure 1c the nearby potential local sources mentioned in the text, such as the city of Freiburg, Hofsgrund, and settlements in the Upper Rhine Plain.
Page 4, line 93 ff: Please clarify whether condensation in the sampling line, upstream as well as downstream of the 2 °C pre-drying unit in winter could occur. If so, please describe how this potential issue is addressed at this site.
Page 4, line 95 ff: While the CRDS instrument measures H₂O in general, this sentence reads as if ambient H₂O is being measured directly. As I understand it, ICOS does not perform calibrated ambient H₂O observations, and a pre-drying unit is installed upstream of the instrument. Please rephrase the sentence for clarity and adjust Table 1 accordingly.
Page 6, line 124 ff: It is unclear what is meant by “quality control” in this context. Please briefly clarify which specific procedures are performed by the station manager after ICOS data processing.
Page 7, line 126 ff: It is not clear whether the concept of “target measurements” (STT and LTT) is familiar to all readers. It may be helpful to briefly explain these terms and include a reference.
Page 7, line 130: The averages agree well. However, a few periods fall outside the WMO/GAW compatibility goals. Could the authors please comment on these deviations? Are there specific time periods (e.g. autumn 2023) associated with higher uncertainties or systematic effects? In addition, please clarify how these uncertainties are accounted for in the subsequent analysis.
Page 7, line 135: The time series shows a data gap in 2022. For clarity, it would be helpful to mention this explicitly in the text.
Page 7, line 143 ff: The mean seasonal cycle is derived by averaging data from three years. Since atmospheric CO₂ and CH₄ concentrations exhibit a long-term increase, it may be helpful to briefly comment on whether this trend could influence the averaged seasonal cycle. While the long-term growth is expected to cancel out for the analysis of the intake differences, it may be relevant when considering the absolute concentrations.
Page 7, line 146: Please explicitly clarify whether the term “LT” includes or excludes daylight saving time (summer time) in your analysis.
Page 8, line 148 ff: Please clarify how this sampling criterion of minimum of three daily means affects the representativeness of the monthly means used in the analysis.
Page 8, line 163 ff: The range between minimum and maximum dry mole fractions is provided. It may also be helpful to include the mean and, in particular, the variability (e. g. standard deviation) to better characterise the distribution.
Page 8, line 165 ff: The potential travel time of the air masses between the two intake locations, as well as the residence time in the sampling lines, is not discussed. It is therefore unclear how the measurements are synchronised to ensure that the same air mass is compared for both instruments. Please clarify how this is accounted for in the analysis and whether it may influence the results.
Page 9, line 171, Fig 4d: While the variability in summer is clearly higher for ΔCO₂, it is difficult to discern similar seasonal differences for CH₄ (Fig. 4d). Including a measure of variability (e.g. error bars) may improve the interpretability of the figure.
Page 10, line 191, Fig. 5: To which averaging time does the WMO/GAW compatibility goal refer? As noted before, please also clarify how the travel time of air masses between the two intake lines is accounted for and whether it may affect the results, particularly in the minute-resolution data analysis.
Page 11, line 198 ff: It is unclear whether the reported values represent the minimum and maximum observations. If so, these may be influenced by individual events and not fully represent the variability during the respective period. Please consider whether a statistical measure such as the standard deviation would provide a more representative characterisation of the atmospheric variability.
Page 14, line 274 ff: The explanation of the CH₄ seasonality is somewhat unclear. The dominant atmospheric CH₄ sink is oxidation by OH, which exhibits a pronounced seasonal cycle on large spatial scales. However, the current discussion appears to mix large-scale processes with regional transport and local source influences. For example, the statement that the sink is more important in summer when CH₄-enriched air masses are transported to the station is not entirely clear and would benefit from further clarification. In addition, it would be helpful to explicitly state which CH₄ sources and sinks are considered and how they are related to solar radiation. In particular, the link between anthropogenic CH₄ sources and solar radiation is not clear.
Page 18, line 344, Fig. 10: The figures also include the baseline extracted using the REBS method (purple line, b= 0), which is stated to overestimate the concentrations (p. 17, line 335 ff). However, even for the selected parameter settings (b=8 and 3), the deviations from the 35 m reference measurements remain substantial (Fig. 10 (d): up to approximately 40 ppb and 20 ppb, respectively). It is therefore not entirely clear why the baseline (b = 0) was not considered in the study and how it would perform in comparison to the reference measurements. Could the authors comment on the performance and limitations of the REBS baseline more explicitly and whether it could be considered as an alternative approach in the analysis?
Page 22, line 411 ff: As the historical measurements have changed from a 6 m to a 12 m inlet height, could this study be used to assess how the long-term time series may be affected by the different sampling positions? A brief discussion of this aspect in the manuscript would be useful for the future interpretation of the long-term record at Schauinsland.
Page 22, line 426 ff: It is mentioned that low-frequency eddy covariance measurements could help to further quantify the influence of the surrounding biosphere. Could the authors briefly explain why conventional eddy covariance measurements are not considered?
Page 23, line 436 ff: It is mentioned that the historical CH₄ record measured at 12 m may be influenced by local pollution, potentially introducing biases in model simulations. Presumably, this issue could also affect the earlier measurements conducted at 6 m. Could the authors comment on the implications for the long-term record and how this issue may be addressed in future studies? It would be helpful if the authors could either provide an estimate of the potential effect or offer recommendations for the interpretation and use of the historical CH₄ record.
Technical corrections:
Page 1, line 23: I suggest to change “Long-term, high precision measurements of atmospheric CO2 and CH4 are essential for monitoring and understanding of global biogeochemical cycles […]” to “[…]are essential for monitoring and understanding global biogeochemical cycles […]”
Page 2, line 24: Change “inter-annual” to “interannual”
Page 2, line 52 ff: Consider clarifying this sentence by explicitly stating that short-term perturbations from local emissions represent an additional challenge for obtaining “representative” long-term atmospheric “background” observations, e.g. “…an additional challenge for representative long-term atmospheric background observations.”
Page 9, line 171, Fig 4: The distinction between the colours and line styles is not clearly visible. Please consider using alternative styles to improve readability.
Page 10, line 191, Fig. 5: The distinction between the blue and orange lines is not always clear, as they overlap during certain periods. Using different line widths (e.g. a thicker line for the one in the background) could improve readability.
Citation: https://doi.org/10.5194/egusphere-2026-849-RC3
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General comments
This manuscript by Großmann et al. presents a comparison between the in-situ CO₂ and CH₄ time series recorded at two different sampling heights at the atmospheric monitoring station Schauinsland (Germany). Schauinsland is one of the global reference sites for greenhouse gas observations and hosts the longest CO₂ time series in Europe. To minimize the potential impact of local perturbations on the measured CO₂ and CH₄ signals, the station—previously operating with a 12 m a.g.l. sampling inlet since 2011—has recently been equipped with an additional inlet at 35 m a.g.l.
This study specifically analyzes the consistency of the CO₂ and CH₄ signals obtained from the two sampling inlets and quantifies systematic biases in the diurnal and seasonal cycles associated with using the higher inlet.
The topic is well within the scope of AMT. The paper is clearly written, the methodology is appropriate, and the results are robust and well described. Moreover, this work represents an important reference for users of the Schauinsland data series. I therefore recommend publication after the authors address the following minor points.
Specific comments
Line 90: What is the inner diameter of the inlet tube, and what is the residence time of air within it?
Section 2.5 (Data treatment): Is the residence time of air in the 70 m long tube of the 35 m inlet considered in the comparison?
Section 2.6 (Robust Extraction of Baseline Signal — REBS) spike detection algorithm: I recommend specifying here the beta and bandwidth values used in evaluating the spike detection method.
Line 181:
“However, on certain days, elevated CO₂ mole fractions are observed at the 12 m intake, occasionally reaching CO₂ enhancements of up to 2 ppm compared to the 35 m intake, most notably during the night of 1 to 2 February 2024 and again on 4 February 2024.”
Could you discuss possible causes for these enhancements that appear only in the 12 m inlet?
Figures 6, 7, 13, S1, S2: Please specify what the error bars represent.
Line 302: Based on the data distributions, it appears that even in winter the differences are skewed toward higher values, suggesting occurrences of elevated CH₄ at the 12 m inlet. What might be the cause? Is the soil snow‑covered during winter?
Line 381: Please provide the fractions of paired data that exceeded the WMO compatibility goal for both the original and the despiked datasets.
Line 411: Has a similar analysis been performed comparing the 6 m and 12 m air inlets?
Line 435: Could you provide recommendations for ensuring consistent use of the historical dataset together with the new 35 m inlet data?