the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Oct 2026
Dust aerosol optical depth at thermal infrared wavelength from an AeroCom/AeroSat study: Comparative analysis and perspectives
Abstract. Mineral dust interacts with Earth’s radiation across a broad spectral range, from near UV to the thermal Infrared (TIR). While global distributions of dust optical depth at mid-visible wavelength (at 0.55 μm, DOD0.55) are well characterized by remote sensing and models, corresponding TIR products (at 10 μm, DOD10) remain limited to a few satellite retrievals and are rarely simulated by models. This coordinated AeroCom–AeroSat study addresses these gaps by presenting the current state of DOD10 using four satellite TIR products, six AeroCom model simulations, a model-based, observation-constrained climatological database, and laboratory measurements of dust properties. The analysis reveals substantial differences in DOD10 across satellite products and models, sometimes exceeding a factor of ten. Discrepancies among satellite products may link to retrieval algorithms and assumptions, while model differences arise from dust emission, removal processes, and mass extinction efficiencies determined by dust optical properties and size distributions. Multi-model mean results indicate that coarse-mode dust (diameter > 2.5 μm) accounts for nearly 80 % of dust mass loading and DOD10 but only about 40 % for DOD0.55. The absence of a reference dataset for DOD10 poses a major challenge, limiting validation to indirect comparisons with proxies such as AERONET coarse-mode AOD0.55, which is informative but insufficient for DOD10 validation. Laboratory measurements of spectral-dependent optical properties highlight the potential of combining shortwave and longwave remote sensing to advance dust compositions analysis through their distinct spectral sensitivities.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
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 26 Nov 2026)
- RC1: 'Comment on egusphere-2026-5264', Anonymous Referee #1, 03 Nov 2026 reply
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- 1
Review of "Dust aerosol optical depth at thermal infrared wavelength from an AeroCom/AeroSat study: Comparative analysis and perspectives" by Dongchul Kim et al.
This study aims to compare satellite data with model results for an optical thickness of mineral aerosols at 10 µm. The goal is to expand our understanding of this variable, which is typically measured at shorter wavelengths in the visible spectrum and at 0.55 µm, as in the case of measurements from AERONET photometers. Adding a second model validation approach using a different wavelength is a good idea. But this addition alone will not solve all the model validation problems at this scale. PM10 is measured by numerous ground-based monitoring networks, and in-situ measurements remain more valuable than column-integrated AOD. Unlike particles with a median diameter of around 0.55 µm, particles with a diameter of 10 µm settle much more quickly, are transported over much shorter distances, and are therefore much more related to sub-grid processes in the models used with Aerocom. The study thus provides additional information, but not necessarily the most useful information for an accurate validation of this type of model.
Based on average climatologies, satellite observations, and modeling, each of which involves significant uncertainties, this article provides an overview of the possible DOD_10 maps. We thus have an assessment of the current state of the art, which is useful for future studies because it provides a range of uncertainty. However, the study, though very lengthy, does not go any further and does not answer the following questions: What is the most realistic dataset available? What is the most realistic model available? What are the best approaches for improving both? So please add some quantifications and discussions on these aspects, which would add value to this article which, for now, is basically just an inventory of what already exists.
Remarks:
Abstract:
Mix between AOD and DOD. And acronyms are not defined. In fact, the use of DOD is obsolete because it dates back to a bygone era when global models only simulated dust due to a lack of development and computing resources. Today, models simulate all aerosols, and the discussion has shifted to AOD.
2. Observational datasets and model simulations
Table1:
- First column is not lon/lat but the horizontal resolution.
- The name is Gillette (not Gillett)
- Change 'multiple' by 'ensemble'
Figure 1: Can you provide a rough estimate of the uncertainty associated with each of the processes? Or, to put it more simply, which processes are the most sensitive in relation to the calculation you ultimately want to perform? The number of bins and the size distribution is probably one of the most sensitive. Why isn't this parameter being studied? If it is because the models are fixed, then there could still be a discussion (with references) on this point.
l.188 please detail this part. Modis and Caliop are obviously not colocated. Could you simply quantify the error done following this procedure? If uncertainty estimates have already been published, please summarize them, as this information will be needed in the discussion that follows.
l.221 The Cesam experiments use aerosols with particle effective diamter between 1.4 and 8.4 um. The present study is about particles with mean mass median diameter of 10 um. Please explain the way to fill the gap.
3. Comparisons of DOD between satellites and models
The Figure 2 shows a good correspondence between model and observations for a three years average. It is not surprising, the most important sources are well-known and studied. The DOD_0.55 are close and it is, for sure, a good result. But can you explain to what extent these similar values might be similar for the wrong reasons (using Figure 1 as an example, for instance)?
l.267 "Differences among satellite products are especially pronounced in Southern Hemispheric source regions and over oceans" Please explain why. And if this can be corrected.
Conclusion:
avoid bullet points and build sentences.
l.623 It is difficult to draw such a firm conclusion given the small number of bins and the poorly suited intervals used by the models presented for size distributions.