the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Sep 2026
Satellite-based constraints on temperature-dependent aerosol–cloud feedback over a clean boreal forest and a rural continental site
Abstract. Temperature-dependent biogenic aerosol formation has been proposed as a negative climate feedback mechanism. However, the indirect cloud-albedo radiative feedback remains difficult to quantify from observations because in situ observations from clouds are sparse and satellite-derived cloud properties are sensitive to retrieval assumptions, cloud regime, and meteorology. In our attempt to tackle this issue, we combine multiyear field observations with carefully sampled satellite retrievals for two diverse locations: a boreal forest site, Hyytiälä in Finland, and a continental site, Southern Great Plains in USA. We focus on low-level liquid clouds and evaluate the impact of sampling criteria (general cloud-quality filters, a local quality filter, and an adiabatic-consistency criterion) and different fitting methods on the estimation of the temperature-dependent radiative effects of biogenic aerosols. We found that if the adiabaticity requirement is not used, the indirect radiative effects are likely underestimated because non-ideal cloud scenes dilute the observed aerosol-cloud response. Based on carefully selected data sets, we estimate that the clear-sky direct radiative feedback caused by biogenic aerosols is approximately -0.6 Wm−2 °C−1 in a clean environment and about half of that (-0.3 Wm−2 °C−1) in a rural region. The indirect radiative feedback of these aerosols is in the same range with the direct radiative feedback (-0.6 Wm−2 °C−1) in the clean region but it is almost three times stronger (-0.8 Wm−2 °C−1) in the rural region. However, the quantification of the temperature-dependent aerosol–cloud feedback is more straightforward in clean environments than in rural ones, where other emissions can drive the aerosol load and number.
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 11 Nov 2026)
- RC1: 'Comment on egusphere-2026-4750', Anonymous Referee #3, 19 Oct 2026 reply
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This paper analyses the temperature-dependent aerosol-radiative feedbacks over two contrasting sites: Hyytiälä, characterized by a relatively clean boreal forest environment, and a rural continental environment of the Southern Great Plains, USA. The authors combined ground-based aerosol measurements with satellite-derived cloud properties to quantify the temperature dependence of aerosol concentrations and aerosol–cloud interactions, and associated radiative feedbacks. Particular attention is given to how the selection of clouds satisfying an adiabatic-consistency criterion influences the inferred aerosol–cloud susceptibility and, consequently, the estimated cloud-albedo radiative feedback.
The paper is well-written, and the overall presentation is good. My only major concerns are around methodology and the uncertainties in the estimated aerosol-radiative feedbacks, as mentioned below.
Major Comments
The Doppler-lidar observations used to prescribe the vertical velocity in the parcel model would be useful to show, particularly the distribution of observed vertical velocities. Also, a prescribed vertical velocity may not sufficiently represent the observed variability in aerosol-cloud interactions, especially at SGP, where stronger updrafts may occur. Furthermore, the differences in using positive Doppler-lidar velocities at Hyytiälä and the standard deviation of vertical velocity at SGP should be explained.
I encourage the authors to simulate the parcel model experiment at different updrafts, e.g., 0.1, 0.3, 0.5 m/s. This would establish whether the model-observation agreement is robust or depends on the selected velocity. Also, I wonder whether the model reproduces the observed CDNC magnitude, in addition to aerosol-cloud susceptibility.
For the adiabatic cloudy conditions, the authors used the difference between effective radii at 3.7 and 2.1 microns. However, can the authors clarify whether the stronger aerosol–cloud susceptibility obtained after applying this criterion reflects the exclusion of clouds inconsistent with adiabatic conditions or partly differences in the cloud populations retained before and after filtering? A brief comparison of the cloud properties between these samples would help support the interpretation.
The temperature dependence of N100 is an important component of the reported radiative feedbacks. However, aerosol conditions can be greatly influenced by meteorological conditions, transport, and wet scavenging. I suggest that the authors clarify or comment on the extent to which these factors could influence the reported aerosol-temperature relationship. This could be particularly crucial for SGP, where multiple aerosol sources are available. A discussion of these uncertainties would help establish the robustness of the inferred radiative feedbacks.
The estimated aerosol-cloud radiative feedbacks are estimated from the observed aerosol-cloud susceptibility and the temperature dependence of aerosol concentrations. However, these calculations account mainly for the changes in cloud albedo associated with CDNC, without considering potential changes in LWC, cloud fraction (or precipitation). I recommend that the authors clarify how these assumptions limit the interpretation of the estimated feedbacks. It can also be useful to mention which sources of uncertainty are included in the reported confidence intervals (CI)?
At SGP, the aerosol-cloud feedback has a wide CI, hence a possibility of considerable uncertainty in its magnitude. Also, the results appear to be sensitive to adiabatic-consistency criteria within the sampling domain. Could the authors discuss how these uncertainties affect the robustness of the inferred feedback at this site? Clarifying the number of observations retained after the different filtering steps would also help assess the statistical reliability of the results.
Minor comments
Abstract: “biogenic aerosols” may imply stronger source attribution than the manuscript observed. Distinguish the measured aerosol-temperature relationships from their proposed biogenic contribution
Sect. 2.2: Please ensure that the terms “adiabatic”, “near-adiabatic” and “adiabatically consistent” are used consistently, because the retrieval criterion may not establish adiabaticity directly.
Sect. 2.4: A brief explanation of the differences in Doppler-lidar measurements between the sites would be helpful and will motivate the physical reasoning behind selecting 0.3 m/s updraft velocity.
Conclusions: Overall well-written. Distinguish the estimated cloud-albedo feedback from the broader aerosol-cloud feedback. Please also consider adding a paragraph or so describing sources of uncertainties that may affect the presented analysis.