| 12 Jun 2026
Hyperspectral camera observations for the determination of aerosol profiles and cloud properties
Abstract. Spectroscopic 2D imaging observations with high temporal resolution are important for the investigation of different atmospheric research topics, e.g. the monitoring of emission plumes from point sources or the radiative effects of rapidly changing cloud fields. Traditional imaging DOAS applications cover one spatial dimension using 2D CCD detectors, while scanning the other dimension by sequentially changing the viewing direction. Several minutes are usually needed to achieve a complete 2D image by such techniques. An alternative with much higher temporal resolution is provided by hyperspectral cameras, which can achieve complete 2D images within a few tens of seconds. The limitations of such observations are sometimes the low spectral resolution (typically a few nanometers) and the rather small field of view (usually covering about 10⁰). Nevertheless, hyperspectral cameras were already successfully used from ground based or satellite observations to derive high-resolution spatial patterns of atmospheric trace gases.
In this study we use a hyperspectral camera covering the visible and near IR spectral range (400 – 1000 nm) with a spectral resolution of about 4.7 nm. We show that the absorptions of O4 can be well determined from the measured spectra. We use the derived O4 absorptions together with the simultaneously measured calibrated radiances to determine atmospheric profiles of the aerosol extinction and cloud properties. Here we exploit one important advantage of the 2D imaging capabilities: the unambiguous distinction between clear and cloudy parts within the recorded image. Such a clear distinction is often impossible from simple 1D elevation scans of typical MAX-DOAS observations.
We derive cloud properties (altitude, horizontal distance and optical depth of scattered clouds) from the 2D images, and aerosol extinction profiles from the spectra of the cloud-free parts of the images. We also investigated potential effects of scattered clouds on the radiation fields between the cloud patches and found that the O4 absorptions and radiances are not significantly affected by the nearby clouds. This is an important finding for the retrieval of aerosol profiles from MAX-DOAS measurements in partly cloudy sky conditions.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
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Review of “Hyperspectral camera observations for the determination of aerosol profiles and cloud properties” by E. Frins et al.
In this manuscript, the authors explore an idea to extract aerosol and cloud information from ground-based hyperspectral images in the visible and NIR. They combine information from the O4 absorption with absolute radiances and geometric considerations to determine an aerosol profile as well as cloud positions and optical depth.
The idea presented in the manuscript is interesting, and the first results are promising. The topic discussed fits well into the scope of AMT. The paper is overall well written, but in some places, information is hidden in tables, figures, or the appendix, which I would rather include in the main text.
Major comments
I have three main concerns about this manuscript:
a) The aerosol profiles shown have many detailed structures, but I guess the information content of the measurements is quite limited. I understand that no formal inversion was performed, but rather a number of scenarios were computed and the best fit selected. Nevertheless, the readers need to have an idea of what the vertical resolution of the derived aerosol profiles is.
b) The use of radiometrically calibrated radiances to constrain total AOD is interesting. However, there must be an uncertainty in the calibration of the instrument, and the authors should provide an estimate of how this uncertainty impacts the AOD values they retrieve. The use of a simplified phase function will also have an effect on the AOD estimates, and this should be evaluated as well.
The same holds for the retrieval of cloud information – which scenarios were evaluated, how was the best selected, which parameters were varied over which range? In a 3d simulation, the number of parameters can quickly become very large, and only some of them can be constrained by the measurements.
In summary, I think this is an interesting exploration, but much more information on the method and the uncertainties needs to be provided before it can be accepted as a manuscript in AMT. If possible, the authors should also add external support for the validity of the aerosol profiles, AOD and cloud parameters they retrieve.
Detailed comments