the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Mar 2025
Quantifying the impact of solar zenith angle, cloud optical thickness, and surface albedo on the solar radiative effect of Arctic low-level clouds over open ocean and sea ice
Abstract. Due to their complex interactions with surface albedo, aerosol particles, and water vapour, clouds play one of the most uncertain roles in the Arctic climate system. Consequently, the cloud radiative effect (CRE), which is a quantitative measure of the impact of clouds on the radiative energy budget (REB), is subject to considerable uncertainty. To reduce this uncertainty and better understand the importance of the driving processes, it is crucial to quantitatively disentangle the various cloud and non-cloud factors that non-linearly affect the CRE. Therefore, this study uses a combination of a CRE parameterization and low-level airborne REB observations to quantify the impact of concurrently observed cloud optical thickness, solar zenith angle, and surface albedo on the solar CRE at the surface. Based on a case study characterized by inhomogeneous cloud and surface conditions in the marginal sea ice zone, the contributions of surface albedo and cloud optical thickness to the solar CRE are derived similar to the approximated partial radiative perturbation technique applied in climate dynamics. It is shown that the surface albedo contributed more than 95 % to the solar CRE difference between open ocean and sea ice. Using the same approach, the analysis was extended to observations from a series of aircraft campaigns, indicating that the non-cloud conditions frequently dominate seasonal and surface-type differences of the solar CRE.
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RC1: 'Comment on egusphere-2025-1210', Anonymous Referee #1, 08 Apr 2025
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“Quantifying the impact of solar zenith angle, cloud optical thickness, and surface albedo on the solar radiative effect of Arctic low-level clouds over open ocean and sea ice” by Becker et al. investigates the relative contributions of cloud properties (summarized as optical thickness) and surface albedo to solar cloud radiative effects using observations made from aircraft during the ACLOUD and AFLUX campaigns. The study concludes that surface albedo overwhelmingly dominates over cloud properties in the difference in observed CRE between ocean and sea ice domains. The study presents some interesting concepts and results. I think it will suitable for ACP with a revision that addresses concerns that are both technical in nature and relate to the overall scoping of the study’s motivation and interpretation.
General Concerns:
- The introduction needs work. It provides a review of the cloud radiative forcing in the infrared, with discussion of solar effects being absent or incidental. It then says the present study doesn’t analyze the infrared, only solar. Seems like the intro should focus on the current state of, and outstanding gaps in knowledge of solar radiation.
- The study is motivated by the need to constrain cloud feedback estimates, but it does not investigate cloud feedbacks at all, despite what the study sometimes suggests, such as at the top of section 4. Fundamental to the feedback concept is a change in cloud properties as a response to some climate forcing, which may, for example, be measured by cloud forcing. Here the concept is conflated with the difference in cloud forcing between when a cloud is over ocean and when it is over ice. Therefore, the “distinct states” referred to throughout the text are not analogous to Taylor et al., Soden et al. etc. Sometimes, these are referred to as “climate states” (e.g., L200), which is more consistent with the referenced literature, and other times as “locations”, “seasons” (L75), or just “states” (throughout), which is less consistent. Regardless, these are not interchangeable concepts. I like the objective here of trying to understand how varying surface and cloud properties result in the CRE that is observed, but the study should not overstate its connection to the problem of cloud feedbacks.
- How many total hours of observations are included here? How many unique clouds are sampled? I suspect the samples are limited. While there are some nice methods and analyses here, we are still working with a few case studies. Therefore, while I agree that similar analyses in the infrared is a good suggestion (L274), the main recommendation for the community should be more studies focused on how cloud and environmental properties combine to produce cloud forcing without the implicit suggestion this is the final word on the solar component. Be careful not to overstate.
Specific Comments:
- L95: Can you provide more information on the profiles? How far away are the soundings? Where they found to be comparable to the aircraft data? How did you merge these data?
- Can you show comparisons between the simulations and observations when the sky was clear to validate the CF estimates? This will help ensure there is not a mean bias in the CRE.
- You state the CRE fluxes are w.r.t. the surface (e.g., line 90), but the observations were made at flight level. As you say at L59-60, water vapor is impactful on the solar, and later at L248 that you flew above some cloud layers. You should use the model to assess whether an atmospheric correction is needed to transfer the observations to the surface, and apply it if it is determined to be significant. Otherwise, you should refer to the calculations as what they are, observations from flight level (and calculate accordingly).
- L111-112: Cloud optical depth is not a property independent from transmissivity. They are different ways of saying the same thing.
- L112: I don’t think it is correct to say multiple reflections actually increase cloud transmissivity, though it would confound your ability to calculate an accurate value using the broadband measurements with e.g., Eqs (4,5).
- L30: This point is somewhat stylistic. Ramanathan et al. (1989) defined “cloud-radiative forcing” (CRF), as the net effect, as your equation states. While the literature is not very consistent about this (partly because at TOA, CRE=CRF), at the surface it is useful to reserve the term CRE for the difference in the downwelling components. Consider changing to “CRF” terminology.
- L30: I think it would be helpful to the reader to include subscripts denoting the fluxes and CRE (CRF) are solar, even though infrared is not analyzed here. In that way, no one will misinterpret the figures if they aren’t paying close attention to the text.
- L32: “quantify the REB in cloud and cloud-free conditions” is not correct. The statement should be “quantify the REB difference between all-sky and cloud-free conditions”. Correspondingly, the “cld” subscript in Eq. 1 and 2 is also not correct: it should be “all-sky”. For example, CRF = ALL – CLR could alternatively be defined as CRF = [CLD – CLR]*FCC, where FCC is cloud fraction. I realize it may be a matter of semantics for your application.
- L50: Not all studies find a cooling effect in summer…Miller et al.
- L111: I’m not certain the best place in the text to do this, but somewhere it would be helpful to state that that transmissivity (and tau) are broadband values.
- L155/Figure 3: can you add the symbols (alpha, tau) to the appropriate axis labels? Perhaps also make it clear that the color-coding from (a) is used also in the other panels.
- L160: SZA still has an impact on CRE, so maybe replace “impact” with “dependency”. I’m not certain what you mean by this sentence because you state that mu will be neglected and then in the very next sentence you set it to a constant. I understand why you made it a constant, but the second statement seems to contradict the first.
- L188: I don’t think this is obvious at all.
Editorial Comments:
L21: “on the one hand” L23;
L25: I think you mean “is expected to” not “will”
L36: “antagonism” is an odd choice of word. “Due to these opposing effects…”?
L111, elsewhere: “suitable”?
L222-223: I don’t understand this sentence. I might be a run-on or something.
L266: This sentence lacks clarity.
L274-275: “an as” to “a”?
Citation: https://doi.org/10.5194/egusphere-2025-1210-RC1 -
RC2: 'Comment on egusphere-2025-1210', Anonymous Referee #2, 25 Apr 2025
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General
Airborne radiation measurements over the Arctic marginal sea ice zone and open ocean near Svalbard are analyzed to investigate the dependence of the cloud radiative effect on solar zenith angle, cloud optical thickness and surface albedo. It is found that the latter has by far the largest effect.
The manuscript is in all parts very well written, it is clearly organized and the topic is of large scientific interest for climate research. The paper addresses one of the most uncertain factors in climate projections, namely the impact of clouds on the surface energy budget. The analysis helps to better understand the complex interaction processes between clouds and the surface due to their effects on radiation. Most of the text can be well understood but I suggest adding some explanations for non-experts. Altogether, these suggestions and some further hints to the text are all minor points and I recommend the publication of this very well done work after revision.
Revisions
- I think, the description around Figure 4 (Caption and corresponding text) can be improved. The meaning of the black dashed line is somehow unclear to me. I guess the red numbers refer to the full change of the Solar CRE between the Open Ocean state and the Sea Ice state rather than to the change from the Ocean state to the intersection point. But this does not become clear. I did not fully understand the meaning of the evaluation point. Following the given numbers (131.6+0.6 = 132.2, 8.3+124.0=132.3, 127.9+4.3=132.2) the way how we come from the open ocean state to the sea ice state plays no role. This should be stressed, if correct.
- Perhaps, a Discussion section could be added where, e.g. the differences between both methods based on equations (10) and (13) are discussed and their different ranges of validity. In this connection Lines 195-210: Is it possible to give a threshold for the validity of (10)? Further possible points for a discussion is the difference to mid latitudes and if the results have any effects on or benefits for modelling.
Hints for text improvement
Lines 10-12: at this point it is perhaps unclear how non-cloud conditions can dominate the cloud radiative effect.
Line 22: define a larger/smaller REB
Line 41: a negative CRE change is a decrease of the CRE?
Line 52: better: solar cooling effect caused by clouds over open ocean?
Line 67: unclear: which parameters?
Line 105: why is the index of the transmissivity of cloud free atmosphere ‘atm’ and not ‘cf’ ?
Line 111: function of alpha and mu
Line 143: better transition of the CRE from … to …
Caption figure 3: the caption text should better fit to what is used in the figure, so either you use abbreviation mu, tau alpha or the complete names. Also, please add the day to which these observations belong.
Line 195: better: two states defined by different values of optical thickness, surface albedo etc.
Line 195: without correlation means here simply large differences between the states?
Please increase the thickness of the green line in the figure.
Line 215: perhaps better: see the pairs of green blue and red numbers ….
Citation: https://doi.org/10.5194/egusphere-2025-1210-RC2
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