the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Sep 2026
Linear tomographic retrieval characterisation and performance estimation for the ESA Earth Explorer 11 candidate CAIRT (Changing Atmosphere Infra-Red Tomography explorer)
Abstract. The Changing-Atmosphere Infra-Red Tomography Explorer (CAIRT) was proposed as a candidate for the European Space Agency’s eleventh Earth Explorer mission to address critical knowledge gaps in middle atmosphere dynamics and composition. Utilizing an innovative Imaging Fourier Transform Spectrometer (IFTS) in a limb-sounding geometry, CAIRT is designed to provide high-resolution, three-dimensional (3D) tomographic observations of the atmosphere from the free troposphere (5 km) to the lower thermosphere (115 km). To support the scientific evaluation and requirement consolidation of the mission, this paper introduces two computationally efficient performance modeling tools: the Linear Performance Estimator (LPE) and the Fast L2 Simulator (FL2S).
The Linear Performance Estimator (LPE) serves as a diagnostic tool that applies linear retrieval theory to quantify spatial resolution and retrieval uncertainties for atmospheric targets like temperature and trace gas concentrations. It features a novel extension to 2D tomographic retrievals, enabling the assessment of how instrument characteristics and uncertainties propagate into final Level-2 (L2) geophysical data products. The Fast Level-2 Simulator (FL2S) complements this by utilizing LPE-derived metrics to project high-resolution atmospheric model data fields onto a simulated CAIRT measurement grid, generating synthetic L2 data products that mimic the full retrieval chain. This allows for a streamlined assessment of how CAIRT’s spatial resolution and uncertainties affect specific scientific use cases.
Applying these tools to the CAIRT instrument characteristics, we demonstrate the mission’s capability to meet specified L2 and science performance requirements. The results confirm that the modular end-to-end simulation framework effectively translates instrument specifications into robust scientific performance metrics, providing a mature basis for possible future implementations of limb-imaging space missions.
Competing interests: At least one of the (co-)authors is a member 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: open (until 30 Oct 2026)
- RC1: 'Comment on egusphere-2026-3881', Anonymous Referee #1, 14 Oct 2026 reply
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RC2: 'Comment on egusphere-2026-3881', Anonymous Referee #2, 16 Oct 2026
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Anonymous Referee Comments
This paper provides a detailed account of the technical and structural efforts undertaken to estimate the scientific performance and retrieval characterisation of the Changing Atmosphere Infra-Red Tomography Explorer (CAIRT), a proposed candidate for the European Space Agency's 11th Earth Explorer mission. Although CAIRT was not selected for implementation, the associated technological and scientific developments remain of high relevance to future mission advancements.
Several minor comments are provided with the aim of further enhancing the readability of this already very well-written paper.
Minor comments:
General:Several acronyms are defined several times unnecessarily (e.g., FL2S, NESR). Refinement on this should be considered.
Text:
L8. Linear Performance Estimator (LPE) previously defined. No need to specify acronyms again.
L43. Correct “e.g.” to “e.g.,”
L49. Previously defined (L2). Inconsistency between Level-2 and Level 2
L53. Previously defined (FL2S).
L59. Include ‘(OSSE)’ after Observation System Simulation Experiments
L60. “Thanks to its computational efficiency, FL2S was used for generating extended time series of simulated observations that can be injected into Observation System Simulation Experiments to assess the scientific or application potential of future data (e.g., Errera et al., 2026)” Are there other examples that can be provided that are not limited to CAIRT?
L244. ISRF refers to Instrument Spectral Response Function? Either change to AISRF or explicitly mention it.
L346. Typo in “L2a”
L364. It might be obvious for most readers but specify UTLS (upper-troposphere low-stratosphere).
L395. Correct “misalignements” to misalignments
L443. Add a comma after “e.g.” -> “e.g.,”
L499. Correct “tropsphere”
Figures:
Figure 2. Describe the meaning of using squares and “magnetic disk”-like symbols. Include the meaning of the acronyms that are not specified.
Figure 5-17 (and Supplement Figures). It might be difficult for some readers to make out the difference between the radiometric additive and NLTE uncertainties and between CO2 and SEDF knowledge. Perhaps changing the line style to dotted or choosing a different colour will help.
Citation: https://doi.org/10.5194/egusphere-2026-3881-RC2
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Referee Comments 14Oct26
Linear Tomographic Retrieval Characterisation and Performance Estimation
for the ESA Earth Explorer 11 candidate CAIRT.
Funke et al., 10.5194/egusphere-2026-3881
Overview
The paper describes some of the preparatory work carried out on
estimating the scientific performance of an instrument proposed for
the ESA EE11 mission.
CAIRT is a limb-viewing FTS building on the heritage of the
Envisat/MIPAS instrument 20 years ago but, as an imaging instrument,
providing a much higher spatial sampling which presents the
opportunity for tomographic retrievals generating 3D global fields of
atmospheric temperature and composition from the mid-troposphere
upwards, comparable to the resolution achieved by numerical models.
The methodology appears robust and the authors have made a good attempt
at explaining the underlying concepts although, I fear, it will
remain a paper fully appreciated by just a few specialists.
Despite making a convincing case, ultimately the CAIRT instrument
was not selected (for EE11). Even so, the paper provides a useful
template for evaluating any future similar instrument and is
scientifically publishable on its own merits.
I have only minor questions, comments and requests for clarification:
L119: Here it says that spectra are calculated from 707-2203 cm-1 compared
to the instrument nominal range 718-2200. I understand the need for some
extension to allow for the sinc-ILS convolution but the asymmetry seems odd
and, bounded on both sides by strong CO2 bands, I am surprised that even
11 cm-1 is sufficient.
L124 says 0.1cm-1 sampling while Table 1 says 0.2cm-1, which is confusing.
It is only in L149 that the discrepancy is explained.
L127: "Jacobians are resampled in the LPE". This makes it sound like a simple
process such as interpolation but changing the vertical grid on which
Jacobians are defined does not seem so straightforward.
L141,142: I have not come across SEDF and AISRF before but I assume the
authors have a good reason for using these terms instead of the more familiar
FOV and AILS?
L156: "Despite" seems the wrong word here. Perhaps "As well as ..." or
"In addition to ...".
L200: Is there a reason why S_m has m as a bold subscript while y in S_y is
regular font? (except in Eqs 8 and 10 where y is also bold?).
L201: Strictly I believe A S should be A S^T here (even though S is symmetric).
L205: You should probably make it clear that S in Eq 7 is not the same S
as in Eq 6.
L221: The minus sign needs some comment - why does a "positive" error in
Delta y lead to a "negative" error in e_sys? I assume it's only relevant when
applying Eq 11.
L231: The Monte Carlo approach seems a little unsatisfactory. It would have been
better to characterise each partly-correlated error with its own covariance
matrix. Admittedly these would be larger than S_y but only by a factor m_h and
you wouldn't need to invert it.
L314: Reference to the "a priori profile" as a constraint is puzzling.
Is that just specific to the CEEPS set-up? The LPE (Eq 2 and L370)
only seems to use Tikhonov regularisation.
Fig 4: Just a comment: I like this plot. It's the sort of result we
often know we *ought* to get but rarely manage in practice.
Table 2: It would have been helpful to reproduce the equivalent numbers
for the primary targets here as well. This sort of information collected
in one place is useful to a wider readership.
L346: What are "L2a" requirements?
L362: I am surprised that you can retrieve a height-dependent
radiometric gain correction which is distinguishable from the
concentration signature of your target molecule in each
microwindow. (Spectral shift and offset are spectrally very different,
so more easily separable.)
Table 4: I suggest including assumed spectral/spatial sampling in the
table caption rather than risk having these figures misquoted by
readers who don't notice the relevant information in L384.
L395: "misalignments" (the only spelling mistake I spotted in the entire paper).
L399/Table 5: What causes "intra-band" relative pointing errors?
L447, Section 3.4
The results show essentially 2D simulations so it is not clear whether or
not you actually ran FL2S for the full 3D coverage in the across-track
direction as well.
Figs 5-13: I couldn't make out the geographical surface features on
the right-hand plots, although there is reference to Japan (L531). It
would be helpful to have another plot showing, say, the location of
the 30km tangent point superimposed on a geographical map. Judging by
the NO/NO2 plots I'm guessing there is also a day-night transition
during this orbit segment, which is probably worth a comment at the
start.
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