the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jun 2025
If the Yedoma thaws, will we notice? Quantifying detection limits of top-down methane monitoring infrastructures
Abstract. Large quantities of carbon are stored in Yedoma permafrost. When temperatures rise, its high ice content is a catalyst for rapid degradation, which in turn may cause the release of large quantities of carbon. 40 % to 70 % of the radiative forcing from this release is expected to be in the form of CH4. In this observing system simulation experiment, we examined the capabilities of three atmospheric GHG monitoring platforms i.e. tall towers, and the TROPOMI and MERLIN satellites, to detect changes in CH4 release from increased Yedoma thaw. A set of environments are simulated with the GEOS-5 model: one representing a 'natural' emission case as the reference, a second featuring enhanced CH4 release from Yedoma soils. From within these modelled environments, synthetic measurements are generated following best in situ practices and realistic error characterizations.
For the satellites we find the lowest detection limits when aggregating measurements over a 112 day period, at Yedoma fluxes of 144 % to 367 % of current conditions. These factors are up to 1.2 times higher when taking transport modelling uncertainties into account. The tall tower network shows a wide range of detection lower limits, the lowest at only 107 % of current fluxes, but has considerably higher lower detection limits when factoring in transport errors. Overall, the individual systems appear to lack the ability to detect and attribute small changes in Yedoma CH4 fluxes, and would either need to be used in combination or require a considerable time to detect changes under higher emission scenarios.
Competing interests: At least one of the (co-)authors is a member of the editorial board of AMT.
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.-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1472 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1472 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-604', Anonymous Referee #1, 24 Jun 2025
- AC2: 'Reply on RC1', Martijn Pallandt, 08 Sep 2025
-
RC2: 'Comment on egusphere-2025-604', Anonymous Referee #2, 09 Jul 2025
- AC1: 'Reply on RC2', Martijn Pallandt, 08 Sep 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-604', Anonymous Referee #1, 24 Jun 2025
General comments
Methane is second most important greenhouse gas in Earth's atmosphere, and a large possible source is melting permafrost. Timely detection of
increased CH4 emission from melting permafrost is therefore an interesting and relevant research question. The authors try to answer that question by performing an OSSE with three observing platforms and increased CH4 emissions from Yedoma soils in the Arctic. The changes in CH4 can be detected and attributed best when the platforms are used in combination or over longer time periods. Since the article adresses a relevant sicientific topic from an instrumentation perspective, it
should be published after consideration of the specific comments given below.The paper uses outdated versions of the EDGAR emission database and TROPOMI retrieval products (see specific comments), without a proper justification. At the very least, such a justification should be added to the paper, but the paper would be more relevant if the OSSEs were based on recent datasets.
Specific comments
*) page 3, line 125: it is mentioned that the model as a 0.5 degree
horizontal resolution. But the horizontal extent is not mentioned,
is it global or regional? Figure 1 and 5 only show latitude >~ 50N.
*) page 3, line 128: Why use EDGAR v4.3.2 (which is apparently from
2017, even though the cited publication is from 2019.
See https://edgar.jrc.ec.europa.eu/archived_datasets) if more
recent versions of the database are available (such as the 2024
version EDGAR_2024_GHG)?
*) page 3, line 136: Why pick 2010 as baseline year? Later TROPOMI data
from 2019 is used for the synthetic data. So you could have used
actual TROPOMI data with measured cloud fractions etc..
What would change if you modelled a longer time period?
*) page 3, line 137: do you only amplify the Yedoma gridcells and keep
the emission from the non-Yedoma grid cells constant?
*) page 5, line 187: although the version numbering of TROPOMI SRON
and operational retrievals could be improved, I think that v0017
is an older version of the SRON retrieval product. Lorente et al.
(2022, https://doi.org/10.5194/amt-2022-255) describe important
updates to the algorithm improving the retrievals. These updates
have since then been incorporated into the operational (reprocessed)
product. The question is therefore, why use an older version of the
product?
*) page 5, line 189: Why use version 1.5 of the WFMD product?
Version 1.8 has been available for years
(e.g. https://doi.org/10.5194/amt-16-669-2023)
while the most recent version is 2.0:
https://www.iup.uni-bremen.de/carbon_ghg/products/tropomi_wfmd/index.php
*) page 5, line 189/190: The sentence "Both of these products only
contain successful retrievals." is incorrect. These products do contain
e.g. non converged retrievals, but you can (and probably should) select
only the successful retrievals with the provided quality flags.
*) page 5, line 199: "... fitting a curve to reported uncertainties..."
Please provide a plot with this fit.
*) page 5~7, sections 2.3 and 2.4: How is the model sampled for satellite
observations? Is the averaging kernel taken into account?
*) page 7, line 256-257: wrt. the t-test, is the test statistic used in
a one or two-tailed significance test, and what about the null and
alternative hypotheses?
*) page 11~13, figures 6~8: why use 28-day bin sizes while in lines
277-279 (page 7) it is mentioned that "for the remaining evaluation
we focus on the 112 day bin..."?Technical corrections
*) page 1, line 3: affiliation of last author (Gockede) is missing.
*) page 1, line 15: please change satellites to satellite instruments.
*) page 2, line 85: since this is the first mention after the abstract
of MERLIN, please provide the full instrument name in addition to
the acronym.
*) page 6, table 1: fix the vertical alignent of the cell "Ice, TROPOMI"
(containing the number 141461)Citation: https://doi.org/10.5194/egusphere-2025-604-RC1 - AC2: 'Reply on RC1', Martijn Pallandt, 08 Sep 2025
-
RC2: 'Comment on egusphere-2025-604', Anonymous Referee #2, 09 Jul 2025
- AC1: 'Reply on RC2', Martijn Pallandt, 08 Sep 2025
Peer review completion
Post-review adjustments
Journal article(s) based on this preprint
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Martijn Pallandt
Abhishek Chatterjee
Lesley Ott
Julia Marshall
Mathias Göckede
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1472 KB) - Metadata XML
General comments
Methane is second most important greenhouse gas in Earth's atmosphere, and a large possible source is melting permafrost. Timely detection of
increased CH4 emission from melting permafrost is therefore an interesting and relevant research question. The authors try to answer that question by performing an OSSE with three observing platforms and increased CH4 emissions from Yedoma soils in the Arctic. The changes in CH4 can be detected and attributed best when the platforms are used in combination or over longer time periods. Since the article adresses a relevant sicientific topic from an instrumentation perspective, it
should be published after consideration of the specific comments given below.
The paper uses outdated versions of the EDGAR emission database and TROPOMI retrieval products (see specific comments), without a proper justification. At the very least, such a justification should be added to the paper, but the paper would be more relevant if the OSSEs were based on recent datasets.
Specific comments
*) page 3, line 125: it is mentioned that the model as a 0.5 degree
horizontal resolution. But the horizontal extent is not mentioned,
is it global or regional? Figure 1 and 5 only show latitude >~ 50N.
*) page 3, line 128: Why use EDGAR v4.3.2 (which is apparently from
2017, even though the cited publication is from 2019.
See https://edgar.jrc.ec.europa.eu/archived_datasets) if more
recent versions of the database are available (such as the 2024
version EDGAR_2024_GHG)?
*) page 3, line 136: Why pick 2010 as baseline year? Later TROPOMI data
from 2019 is used for the synthetic data. So you could have used
actual TROPOMI data with measured cloud fractions etc..
What would change if you modelled a longer time period?
*) page 3, line 137: do you only amplify the Yedoma gridcells and keep
the emission from the non-Yedoma grid cells constant?
*) page 5, line 187: although the version numbering of TROPOMI SRON
and operational retrievals could be improved, I think that v0017
is an older version of the SRON retrieval product. Lorente et al.
(2022, https://doi.org/10.5194/amt-2022-255) describe important
updates to the algorithm improving the retrievals. These updates
have since then been incorporated into the operational (reprocessed)
product. The question is therefore, why use an older version of the
product?
*) page 5, line 189: Why use version 1.5 of the WFMD product?
Version 1.8 has been available for years
(e.g. https://doi.org/10.5194/amt-16-669-2023)
while the most recent version is 2.0:
https://www.iup.uni-bremen.de/carbon_ghg/products/tropomi_wfmd/index.php
*) page 5, line 189/190: The sentence "Both of these products only
contain successful retrievals." is incorrect. These products do contain
e.g. non converged retrievals, but you can (and probably should) select
only the successful retrievals with the provided quality flags.
*) page 5, line 199: "... fitting a curve to reported uncertainties..."
Please provide a plot with this fit.
*) page 5~7, sections 2.3 and 2.4: How is the model sampled for satellite
observations? Is the averaging kernel taken into account?
*) page 7, line 256-257: wrt. the t-test, is the test statistic used in
a one or two-tailed significance test, and what about the null and
alternative hypotheses?
*) page 11~13, figures 6~8: why use 28-day bin sizes while in lines
277-279 (page 7) it is mentioned that "for the remaining evaluation
we focus on the 112 day bin..."?
Technical corrections
*) page 1, line 3: affiliation of last author (Gockede) is missing.
*) page 1, line 15: please change satellites to satellite instruments.
*) page 2, line 85: since this is the first mention after the abstract
of MERLIN, please provide the full instrument name in addition to
the acronym.
*) page 6, table 1: fix the vertical alignent of the cell "Ice, TROPOMI"
(containing the number 141461)