the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Mar 2024
WRF-SBM Numerical Simulation of Aerosol Effects on Stratiform Warm Clouds in Jiangxi, China
Abstract. Aerosols, as cloud condensation nuclei (CCN), impact cloud droplet spectrum and dispersion (ε), affecting precipitation and climate change. However, the influence of various aerosol modes on cloud physics remains controversial, and this effect varies with location and cloud type. This study uses a bin microphysics scheme (WRF-SBM) to simulate a warm stratiform cloud in Jiangxi, China. The numerical simulations reproduce the macro and microstructure of warm clouds compared with aircraft observations. Further experiments modifying the aerosol spectrum and number concentration indicate: increased aerosol concentration promotes cloud formation, raises cloud height, and broadens the cloud droplet spectrum. In contrast, a decrease in aerosol concentration suppresses cloud formation and development. Different aerosols have varying effects on the cloud droplet spectrum. Higher accumulation mode aerosol concentration increases small droplet concentration, while increased nucleation and coarse mode aerosol concentration favors larger droplet formation. Generally, the correlation between ε and volume-weighted particle size (rv) changes from positive to negative as rv increases. The transition in correlation is influenced by the relative strengths of cloud droplet collision, condensation, and activation processes. The increase in accumulation mode aerosol concentration strengthens the positive correlation between ε and rv in the rv range of 4.5–8 μm, while the decrease in concentration strengthens the negative correlation in the same range. Regardless of different coalescence intensity, ε converges with the increase in Nc. Changes in aerosol concentration for different modes do not alter the convergence trend of ε-Nc but only affect the dispersion of ε at low Nc levels.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2023-2644', Mónica Zamora Zapata, 30 Mar 2024
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RC2: 'Comment on egusphere-2023-2644', Anonymous Referee #1, 06 Apr 2024
Review comments of “WRF-SBM Numerical Simulation of Aerosol Effects on Stratiform Warm Clouds in Jiangxi, China” by Li et al.
General comments
This study uses a bin microphysics scheme (SBM) in the WRF model to simulate a warm stratiform cloud case in Jiangxi, China. It is found that the numerical simulations mostly reproduce the macro and microstructure of warm clouds when they are compared with aircraft observations. Five additional numerical experiments modifying the different modes of aerosol spectrum and the number concentration are carried out and the relationship between Cloud droplet spectral relative dispersion (ε) and volume-weighted particle size (rv) are found to be varying with the volume-mean radius. The results look interesting and improve the understanding of the impacts of different aerosol modes on stratiform cloud properties. But this paper definitely needs much clearer descriptions to some key issues and explanations to several questions.
Specific comments
- The title of this paper seems quite conventional and covers a broad area of Aerosol Effects on Stratiform Warm Clouds. The authors could consider narrowing the area to the more specific focus of this study, which could more accurately reflect the contents of this paper.
- In the abstract, several important symbols and abbreviations are used without definition, i.e., ε and Nc, which makes it difficult for the readers to understand the meaning.
- The authors should consider re-arranging the introduction part and combine the paragraphs about the same topic. Line 48-53 is suggested to move forward before discussing the “cloud droplet spectrum correlations”. Overall, there is a lack of a clear descriptions of what has been done, what remains uncertain, and what needs to be done, especially what is to be solved in this study. There is also a lack of description on the related research about the target area – Jiangxi, China or eastern China.
- The authors should have added a section in part 2 to describe the data used for validation purpose. The flight observations and FY2G satellite observations should be described in more details. This is very critical point.
- Please explain how you determine the analysis range (the red box in Fig. 1). Maybe it is related to the flight tracks?
- The authors set the numerical simulations with aerosol concentrations of 5 times of the original value. Do you have some clues on why 5 times is a reasonable choice?
- Section 3.1: the validation part seems not very convincing. Considering the scales of aerosol-cloud microphysical processes, the FY2G observation may be too coarse. FY4A or Himawari-8 observations may be a more suitable substitute.
- The A1A2B1B2 style numbering of Figure 5 etc., is really confusing and inconvenient. Please consider a change. Additionally, what’s the spatial resolution in Figure 5? Why the A1 and B1 panels seem to have very different spatial resolutions?
- Figure 6: How do you define the “normalized height”? The authors described the “Still, the magnitudes of the number concentrations of the control experiment and the observation are generally consistent. Additionally, the average particle size in both groups increases with height, and their vertical distribution trends are consistent.” But to me, the simulation and the observation are far from “consistent” no matter in terms of magnitude or vertical distribution pattern. Please double check. Moreover, the observation-simulation comparison should have been carried out in higher temporal resolution, i.e. hourly, for better illustrations of the cloud property variations.
- Figure 10: what is “cloud-rain auto-conversion intensity (T)”, or “cloud droplet collision and coalescence intensity (T)”? Why the terms are different in the main text and in Figure 10 caption?
- Line 280-294: You may consider combing the paragraphs as they are discussing the same point?
- Line 340: “This difference may arise from variations in cloud height and cloud water content.” – please explain more.
- Generally, the reviewer has an impression that the descriptions and discussions in the main text are not very consistent with what can be seen from the figures. Suggest to double check.
- Many typos and grammar mistakes are found (see minor points) but much more needs to be found. A thorough proofread is badly needed.
Minor points
- Line 28: The authors should be careful with their narration. They say “many researchers” but only give 2 references, which is not very convincing. Additionally, the authors should have described the 2 references in more details before they blame on the references to be overlooking something.
- Line 38: What is “macroclimate”?
- Line 39: “cloud droplet spectrum correlations” – correlations between what?
- Line 48: “its variations” – what do you mean?
- Line 54: “In recent years,” – how recent do you mean? 2010 and 2019 covers a decade, and is not very recent to 2024. Similarly, Line 58 “currently” is not suitable to reference 2016, 2018, and 2019. This will confuse the readers.
- Line 105: “Apart from aerosol concentrations” – I think you mean “except for”, please check.
- Figure 2: “the area within the red box indicates the starting point of the flight.” – this is too rough to be understood. You should give the full information about the flight observations, not only the starting point. Please provide more details (full flight tracks, etc).
- Line 114: Out of curious, how do the authors consider the spin-up of WRF simulation, give the simulation period is relatively short here?
- Line 142: “computed using supersaturation”?
- Line 212: “more small cloud droplets” – more cloud droplets of small sizes?
- Line 259: “which defined as” – is defined as
Citation: https://doi.org/10.5194/egusphere-2023-2644-RC2
Data sets
Satellite, Aerosol, and Numerical Simulation Dataset in Jiangxi, China Yi Li, Xiaoli Liu, and Hengjia Cai https://www.scidb.cn/s/NBZFB3
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