the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The evolution of warm rain in trade-wind cumulus during EUREC4A
Abstract. In this paper measurements are presented of the observed properties of aerosols and microphysics of clouds associated with the characteristics of precipitation in convective clouds that formed off the east coast of Barbados during EUREC4A. Most data were gathered by the instrumented British Antarctic Survey Twin Otter aircraft supported by detailed in-situ aerosol measurements at the Ragged Point observatory on Barbados as well as HALO and PoldiRad radars, dropsonde and satellite data. The development of precipitation was studied in the three aerosol regimes previously reported, i.e. one low aerosol regime and two containing desert dust that had been advected across the Atlantic Ocean. The later dust event also contained evidence of biomass burning aerosol. Results showed that the maximum intensity of rain was similar for all the aerosol regimes. Clouds that developed in an environment with high aerosol loading tended to be deeper than those that developed in the clean environment. It was also found that the greatest intensities occurred in clouds that had aggregated, in agreement with previous work.
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RC1: 'Comment on egusphere-2024-142', Anonymous Referee #1, 13 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-142/egusphere-2024-142-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-142', Anonymous Referee #2, 04 Jul 2024
The evolution of warm rain in trade-wind cumulus during EUREC4A
This paper characterizes the thermodynamic and microphysical variabilities within shallow trade cumulus clouds near Barbados, primarily using aircraft observations from the EUREC4A campaign in 2020. The study analyzes shallow cumulus precipitation structures in relation to aerosol loadings and cloud mesoscale structure. Key findings show that maximum rain intensity is associated with cloud aggregation rather than aerosol loading, though aerosols impact cloud depths. The in-depth characterizations of aerosol-cloud microphysical and macrophysical processes using various in-situ and remote sensing platforms are valuable for future modeling studies and the broader shallow cloud research community.
However, the paper currently lacks structure and logical flow. The paragraphs do not transition smoothly, and the objective of the paper is not clear until much later in the text. Some major revisions are necessary to improve clarity and readability. Below are some major and minor comments that suggest more organization and some clarification regarding key results. With this, I am recommending a major revision.
Major comments:
- The premise of the paper should be clarified early in the introduction. The interest in examining the effects of aerosol on precipitation intensity in different conditions and clustering should be stated upfront. Reorganize the introduction into three broad sections: Research topics and science interests, previous works and their highlighted results, and current research objectives. In general, ensure each paragraph and sections end with statements leading to the next paragraphs and sections. This will help improve the readability and comprehension.
- Include all instrumentation and measurement details in section 2. Include the wind and temperature measurements description that is in section 3 right now. Elaborate the Twin Otter and HALO flight details, days, number of flights, duration, distance between HALO and TO flights etc. Write the abbreviations of all the instruments, campaign, satellite etc. used in this study. Currently, many of them are just mentioned as acronyms.
- Section 2 includes all the microphysical probes on board the TO. However, the only ones used in this paper are PCASP and CDP. Could the analysis include the precipitation rates and precipitation drop size distribution evolution from clean to polluted cases using the 2DS and HVPS samples? This could confirm the linkage of aerosol loading and precipitation intensity using independent platforms.
- Expand the discussion to link findings to tie it up with introduction. State the limitations of the approach and suggest the scope and need for future research.
Minor comments:
- Line 41: Write the full form of EUREC4A here since you mention it for the first time. State that the manuscript is based on the EUREC4A datasets.
- Line 50: “The motivation for previous projects and the work presented in this paper focus on the importance of the cumulus clouds in the trade wind region around Barbados and the difficulty they pose for models that need to parameterise clouds and atmospheric properties in such environments.” Clarify how your motivation and objective add to previous studies, the differences in methodologies, timescales, study areas, if any.
- Line 143: The wind and temperature measurements are described in section 3. It should be part of section 2 along with all the other instrumentations.
- Figure 8: The dust aerosols described throughout the manuscript is referred to as ‘silicate (mineral marker)’ in the legend. Adding ‘dust aerosol’ in the legend will be helpful. Similarly, add ‘biomass’ in the legend as well beside ‘organic’ for consistency.
- Figure 8: Change ‘LAAPTOF’ in the figure description to ‘LAAP-TOF’ for consistency.
- Line 186: “The Twin Otter aircraft performed fly-by manoeuvres of RP during each of its flights and agreement between aerosol measurements made by the aircraft and at BCO (not shown) were found to be generally excellent across a range of different instruments and measurement techniques”. Could the list of instruments at BCO used for this verification be listed in section 2?
- Figure 9: The percentiles of the CDP concentration could also be included on the y-axis. Mention if each point is representative of each flight.
- The HALO flights and instrumentations including HAMP used in this study should also be included in section 2.
- Figure 10a: There is only one panel, so ‘a’ should be removed.
- Line 237: Rephrase “For example, the dust that is transported in a relatively deep layer across the Atlantic Ocean from Africa.”
- Line 249: Is the higher CTH spread for 9 Feb compared to 2 Feb case linked to the presence of biomass and dust?
- Use CTH instead of cloud-top heights consistently.
- Line 264: Could the reflectivity at the lowest radar range gate be used to see if aerosol concentration (Na) still does not correlate with reflectivity? Additionally, could the 2DS and HVPS observations mentioned in section 2 be used to compute rain rates, and then correlated with Na to re-confirm this result?
- Figure 13: What is the altitude of radar reflectivity shown in the figure? In Figure 11, the radar reflectivity closest to the surface seems to have higher reflectivity on 2 and 9 February compared to 28 Jan and 13 Feb. If so, then could the cloud base reflectivity (and hence rain intensity) be correlated with Na? A scatter plot showing the cloud base reflectivity/rain rate/CTH vs Na would be more intuitive (instead of time series) for emphasizing the key points here.
- For figures 10 and 13, include the correlation coefficients between Na and CTH and reflectivity for low and high Na It is hard to follow the boxplot median lines as a function of GRIMM N.
- Figure 14: Could the panels be arranged by date or Na for better readability?
- Line 300: “However, the two groups achieve similar maximal values regardless of the initial conditions at cloud base and rate of increase with altitude.” This line contradicts the paragraph at line 286. This earlier paragraph says that the Reff is similar at cloud base but the rate of increase in Reff is higher in low Na But line 300 conveys that regardless of initial (Reff) conditions at cloud base, the rate of increase is the same. Could this be clarified?
- Paragraphs after line 313 do not fit into the section 6 headline. Use new section for this.
- Tie the Figure 16 and 17 results with the previous results. For more context, the essential features (e.g., reflectivity, spatial width, rain rates) of the mesoscale structures (fish, flower, gravel, sugar) should be defined in the introduction. Later, in the results sections the dates featuring each of these structures should be indicated both in text and figures.
- What is the significance of the x- and y- axis in Figure 16? Is the shape of the map indicative of anything? Some clarity would be helpful for readers not acquainted with neural networking.
- Figure 17 and paragraph at line 327: How does this figure tie in with the previous sections? Among all the days shown in the figure, 13 Feb with fish clouds seems to have the least rain rate for a given area. However, in the previous paragraph fish clouds are linked with higher reflectivity which should be a proxy for higher rain intensity. Clarification will be helpful.
- Why are the other days described in the rest of the paper (26,28,31 Jan, 2,5 Feb) not shown in Figure 17?
Citation: https://doi.org/10.5194/egusphere-2024-142-RC2
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