the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Variability of ice supersaturated regions at flight altitudes: evaluation of ERA5 reanalysis using IAGOS in situ measurements
Abstract. Contrail cirrus is one of the largest contributors to aviation's radiative forcing, which arises from long-lived persistent contrails. Avoiding persistent contrail formation has been suggested as a measure to reduce the climate impact of aviation, requiring accurate forecasts of ice supersaturated conditions, i.e. where the relative humidity over ice (RHi) exceeds 100 %. Numerical weather prediction (NWP) models often underestimate or do not account for ice supersaturation. This study evaluates ice supersaturated regions (ISSRs) in the ECMWF ERA5 reanalysis using In-service Aircraft for a Global Observing System (IAGOS) measurements over tropical and extratropical regions in the upper troposphere and lower stratosphere for the period 2011–2022. It considers cloudy and clear-sky conditions and how North Atlantic weather patterns affect the ERA5 ability to predict ISSRs. ERA5 generally underestimates ISSR occurrence due to a dry bias in RHi; the equitable threat score (ETS) is 0.2–0.4, indicating a weak to mediocre relationship with IAGOS. Clear-sky conditions result in an ETS of 0.05-0.18 and generally below 0.1 in cloudy conditions, indicating an almost random relationship. The latter is the result of the saturation adjustment used by the NWP model underlying the reanalysis. North Atlantic winter weather patterns appear to affect the ability of ERA5 to predict ISSRs, particularly along eastbound routes. This may result from varying ISSR distributions relative to the jet stream. North Atlantic summer weather patterns show little impact due to weaker teleconnection patterns. Overall, the underestimation of ISSRs in ERA5 is most critical in the upper troposphere, where their occurrence is highest.
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RC1: 'Comment on egusphere-2025-3048', Anonymous Referee #1, 10 Sep 2025
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3048/egusphere-2025-3048-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2025-3048-RC1 -
RC2: 'Comment on egusphere-2025-3048', Anonymous Referee #2, 29 Sep 2025
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Review of „Variability of ice supersaturated regions at flight altitudes: evaluation of ERA5 reanalysis using IAGOS in situ measurements by Hildebrandt et al., 2025
The present study by Hildebrandt et al. uses the IAGOS water vapour data as a reference to investigate the ability of ERA5 to predict ice-supersaturated regions. The manuscript is generally good, with appropriate methodology for the comparisons of ERA5 and IAGOS. The authors provide an update and a more comprehensive evaluation, both temporally and spatially, compared to previous publications. The results found are described and compared with the results of the earlier studies. A deficit is that there is often only confirmation of the earlier findings without any real new insights being gained. Although this update is certainly of relevance, the manuscript would benefit from being shortened and centered on the relevant results. Thus, I would overall recommend publication but only after major revisions.
Major Comments:
This study demonstrates a significant investment of time and effort, application of recognized methods, and extensive knowledge of IAGOS and ERA5, making the foundation of the study solid. However, the analysis itself is overly descriptive. Often minor differences between the old and new results are shown, regardless of their significance. Therefore, I recommend shortening the text and focusing more on relevant aspects.I don't think it makes much sense to calculate the ETS for many different situations when the poor agreement between the ISSRs found by ERA5 and IAGOS is due to the adjustment scheme under cloudy conditions. I would recommend repeating this part of the analysis by using a threshold of ERA5 RHi of 90 % or 95 % to determine ISSRs (at least under cloudy conditions).
I also have to question the calculation of ETS in the context of discussing different weather patterns. Before discussing the differences in ETS, it would be helpful to examine the fraction of ISSRs for these weather patterns as observed by IAGOS, and determine if there are any differences among them.
It is an interesting feature that in South Asia you find the minimum temperature 60 hPa below the thermal tropopause. The structure of the lapse rate and cold point tropopause in the tropics can be quite complicated but, normally, if there are multiple tropopauses the cold point tropopause is above the WMO thermal tropopause (also in Muhsin et al., 2018?). I suggest performing a literature review to learn more about this. See for example: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2011JD016637
Line 334 and 516: “Therefore, the moist bias appears to arise as a result of the saturation adjustment, which cannot take into account that the (wet) mode of the RHi PDF can be subsaturated in some regions.” In my opinion this should not lead to a moist bias but to an alignment, because the (false) saturation adjustment would just not happen. Please explain.
Specific comments:
Line 123: In IAGOS RHL > 100 % is flagged invalid.
Line 131: Why does sampling every minute result in 2.5% of all IAGOS measurements?
Line 182: You find a higher frequency of indeterminate and cloudy conditions compared to IAGOS because of the limitations of the BCP (see Petzold et al., 2017).
Line 202: Yes, physically, relative humidity partially depends on temperature, but the ICH sensor from IAGOS measures RHL, so, this is the water variable which is independent from the temperature.
Line 205: Please specify how big the ERA 5 cold bias in the extratropics is.
Line 212: “extratropical seasonal cycle“: in the Northern Hemisphere
Line 250: it does not provide good quality results in dry conditions in the lower stratosphere due to the loss of sensitivity as a result of the adiabatic compression effect (Konjari et al., 2025)
Line 302: Please rephrase: “The tropopause layer is not completely dry (Petzold et al., 2020; Reutter et al., 2020)”
Petzold et al. state: “a tropopause layer characterized by mean RHice of 60% almost independent of the season…”
Reutter et al. state: “In the tropopause layer, still a significant amount of the data is exceeding values of RHi > 100 %, both in the in situ data as well as in the ERA data set.”
Line 314: “For clear-sky conditions, there is a smaller probability of low RHi, with increased probability of higher RHi, and a more equal probability across all observed RHi values.” I don’t understand this sentence.
Line 341: typo: “ERA5 may predict less ISSRs compared to ERA5”
Line 364: Delete the word “but” in: “On the other hand, Reutter et al. (2020) found a maximum of 40% using IAGOS when considering all seasons, but with the maximum also occurring 30 hPa below the tropopause and a reduction of the ISSR fraction to zero in the lower stratosphere.
Line 367: “ISSR fraction is highly sensitive to…”: Maybe better without the word “highly”
Line 402: Could the reason for higher ETS in North America be, that there are more data assimilated for ERA5?
Line 407: Please rephrase: “the maximum difference between seasons is approximately 10%, at most. In North America, we find that the variation can be up to 20%.”
Line 410: “tend to find”
Citation: https://doi.org/10.5194/egusphere-2025-3048-RC2
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