the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Oct 2023
Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions
Alejandro Baró Pérez
Michael S. Diamond
Frida A.-M. Bender
Abhay Devasthale
Matthias Schwarz
Julien Savre
Juha Tonttila
Harri Kokkola
Hyunho Lee
David Painemal
Annica M. L. Ekman
Abstract. Biomass burning plumes are frequently transported over the Southeast Atlantic stratocumulus deck during the southern African fire season (June–October). The plumes bring large amounts of absorbing aerosols as well as enhanced moisture, which can trigger a rich set of aerosol-cloud-radiation interactions with climatic consequences that are still poorly understood. We use large-eddy simulation (LES) to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer (MBL) evolution and the stratocumulus to cumulus transition (SCT) for three different meteorological situations over the Southeast Atlantic during August 2017. For all three cases, our LES shows that the SCT is driven by increased sea surface temperatures and cloud-top entrainment as the air is advected towards the equator. In the LES model, aerosol indirect effects, including impacts on drizzle production, have a small influence on the modeled cloud evolution and SCT, even when aerosol concentrations are lowered to background concentrations. In contrast, local semi-direct effects, i.e aerosol absorption of solar radiation in the MBL, causes a reduction in cloud cover that can lead to a speed-up of the SCT, in particular during daytime and during broken cloud conditions, especially in highly polluted situations. The largest impact on the radiative budget comes from aerosol impacts on cloud albedo; the plume with absorbing aerosols produces a total average net radiative cooling effect between -4 and -9 W m-2 over the three days of simulations. We find that the moisture accompanying the aerosol plume produces an additional cooling effect that is about as large as the total aerosol radiative effect. Overall, there is still a large uncertainty associated with the radiative and cloud evolution effects of biomass burning aerosols. A comparison between different models in a common framework, combined with constraints from in-situ observations, could help to reduce the uncertainty.
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Alejandro Baró Pérez et al.
Status: final response (author comments only)
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RC1: 'Comment on egusphere-2023-2070', Anonymous Referee #1, 14 Nov 2023
Review of "Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions." by Pérez et al. 2023 for ACP
This study examines the impact of biomass burning plumes on marine low clouds and the lower troposphere during the Stratocumulus-to-Cumulus transition in the Southeast Atlantic using LESs of three different cases selected from a field campaign. In particular the authors tried to distinguish between the impacts of direct/semi-direct and indirect effects of aerosols as well as the effect of moisture anomalies in the plumes through carefully designed experiments. I think the paper is in general well-written. I vote for minor revision and below is a list of minor comments for the authors to consider:
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Starting on Line 35, this explanation of the deepening-warming mechanism during SCT seems quite unclear to me: (1) it sounds strange to say "latent heat fluxes ... are positively buoyant", (2) it is not entirely true that "...the entrained air is positively buoyant...". There are quite a lot of papers on the possibility of "buoyancy reversal" when dry FT air mixes with cloudy air near the cloud top ..
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Line 91: "This delay ...", I don't know what "delay" this is ...
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Line 106: Are you emphasizing some kind of difference between "diurnal" and "diel"?
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Line 123: "However ...": I am not an expert on this. What if there are more than one aerosol in one droplet of rain due to collision etc.?
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Line 141: This divergence is the same for all cases, all heights and all times?
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Line 330: "The largest impact on the drizzle production ...": This case also just has the most aerosols in the PBL. Isn't that a stronger impact than humidity?
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Line 336: "However, due to ...": Please elaborate a little here on the difficulty as this is quite important ...
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I feel like towards the end of the paper the impact of the direct and semi-direct effects is toned down a little ... Why? I think this is an important thing I learned from the paper as a non-expert on aerosols.
Citation: https://doi.org/10.5194/egusphere-2023-2070-RC1 -
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RC2: 'Review of egusphere-2023-2070', Anonymous Referee #2, 29 Nov 2023
This paper uses four LES simulations over the SEA, initialized according to three cases observed via aircraft in August 2017, to evaluate the relative influence of BB smoke, humidity, and radiative effects on the underlying clouds (stratocumulus-to-cumulus transition). The work is interesting, relevant to ACP, and overall well-written; I have some suggestions for largely minor revisions before final publication.
Major comments:
- This may be beyond the scope of this paper, but the authors in a couple places effectively note noise in the results (e.g., L337 “due to the small and inconsistent differences [between two cases], it is difficult to make a robust assessment…”). Have you performed any sensitivity tests, e.g. slight perturbations in the initial conditions to try to better get a better understanding of the significance of the inter-scenario uncertainties?
- Much of the discussion focuses on the differences between two (or more) different cases to isolate the different aerosol effects; in some cases it’s rather difficult to see these interpretations (specifically Figs 8, 9, and 11). I wonder if it would be too busy to e.g. add a panel to to Fig 11 to show the SW heating differences (from the discussion on L320) for each set of differences/effects, rather than e.g. trying to remember which colors are differenced to isolate just indirect effects. In a few places the wording on these differences could have been more straightforward, e.g. L285 “the decrease in cloud cover in CTRL compared to aer-rad-off” as written isn’t clear whether you mean to highlight a decrease in cloud fraction (or altitude?) over time (differently for the two scenarios) or that CTRL has less cloud than aer-rad-off on all three days. Another instance is L344 “SW CRE generally decreases when comparing CTRL with N100”—not very clear whether this refers to changes over time or between the two. Alternatively, plotting the differences in Fig 8 might help to clarify the meaning, but runs the risk of being too busy.
- Relatedly, in the discussion of quantifying the distinct effects (Table 4), I found myself wishing for a figure to better digest the findings. Perhaps some key differenced parameters from one of the earlier figures, or this table converted into stacked bar plots to show the relative radiative effects relative to one another? Another option would be shaded backgrounds in Table 4, if that’s a format allowed in ACP. Just a thought that might help to better illustrate the results.
- The SEVIRI cloud values (especially cloud fraction) deviate significantly from the simulated conditions (e.g. Fig 5). The authors mention that there are relatively “few values per time,” and it’s expected to have satellite cloud retrieval gaps over the SEA, but a better sense of how much data are actually going into these figures might be helpful. Relatedly, are there specific criteria for what trajectories are considered “relatively close” for averaging purposes? (L255).
- It would be useful to cite Cochrane et al., 2022 (https://doi.org/10.5194/amt-15-61-2022) in the discussion section as well. Admittedly the framing is a bit different, but considering both are using data from August 2017 in the southeast Atlantic, it would be interesting to place the time-evolved heating rates presented here in the context of their observationally-constrained aerosol and water vapor heating. Specifically how one might reconcile the differences between this paper’s Figure 11 and the more vertically-distributed heating rates (their Fig 7).
- Any idea what’s happening with DRY’s precip (Fig 7g-h) with that uptick on the last day (particularly AUG03)?
Minor comments:
- I felt that the paper seemed to jump around a bit in terms of the figure discussion. The figures are all referenced in order of first mention starting in Section 3.1, but the actual scientific discussion (Sec 3.2, 3.3) jumps through Figs 5, 10, 2, 5, 11, 7, 2, 11, 6, 5… I understand why the authors have organized the discussion by parameter, and each set of effects is illustrated by different figures so maybe this can't be helped, but it makes the full picture a bit hard to understand without a lot of scrolling. Another suggestion for flow and readability would be to more explicitly label sections 3.3-3.5 with the case differences (i.e., L191-193), to better interpret the relevant differences when jumping around between the different figures (or conversely, somehow identify the panels/curves in the figures by their relevance to e.g. “aerosol indirect effects,” which I essentially already suggested in the second comment from the top). But these are just suggestions that might further improve an overall decent paper.
- There’s some discussion of the definition of SCT being a “soft” reference (L454) but nonetheless a reference that the authors use—I might suggest a vertical line or an arrow to indicate where this threshold is met on Figs 2-4 (but especially Fig 4) in each case.
- L175: “due to a combination of…” shouldn’t this also include direct effects as “all aerosol effects combined” (L193)?
- L192: “negligible semi-direct aerosol effect”—why is this, if that’s included (excluded) with direct effects in aer-rad-off? Especially since L340 argues that semi-direct effects are more important than indirect effects in (I think) the differencing of those two scenarios.
- L200: suggest to define your SW/LW wavelength ranges here, or at L194.
- L206: “geostationary”
- If it’s not too much trouble I might recommend to flip the orientation of Figs 2-4 and 11, so that simulations are rows and dates are columns, to match the layout (dates = columns) used in Figs 5-9.
- L445: “considered that the cloud cover should remain below 50%” I’m not sure I follow this meaning, but I’m not familiar with the particular study being referenced.
- Fig 10: are the MIMICA curves for CTRL, or for the average of all experiments (but Fig 4 suggests changes in clouds among the different scenarios). If it’s the latter, I’d suggest adding uncertainties to each date; if it’s the former just clarify that in the caption.
- While reading on a mobile device (iOS) I made a comment that I’d like to see ranges on the SEVIRI cloud values in Fig 10, but in opening the .pdf on a PC, I see the authors have already provided this! I’m not sure what quirk of technology made my iOS copy of the figure lose the red shading (even after re-downloading-- maybe something strange with the vector graphics?) but I hope the authors and/or editorial team can ensure this is rendered properly on all devices during final publication. I mention it just because this isn’t an issue I’ve seen before. All that aside, it would be good if the caption would describe what’s shown by the shading (1 standard deviation in CLAAS-3?)
- Throughout: double-parentheses in citation formats (e.g. L26, L60, L212…).
- L110: missing period
- L379: suggest comma after “indirect effect” for list clarity
- L385: Table 4 shows
- L404: suggest maybe “conditions” rather than “periods,” since it’s really just three days.
- L439: above the MBL caused
Citation: https://doi.org/10.5194/egusphere-2023-2070-RC2
Alejandro Baró Pérez et al.
Alejandro Baró Pérez et al.
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