the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Sep 2024
Modeling CMAQ dry deposition treatment over Western Pacific: A distinct characteristic of mineral dust and anthropogenic aerosol
Abstract. Dry deposition plays a vital role in the aerosol removal process from the atmosphere. However, the chemical transport model (CTM) is sensitive to the dry deposition parameterization and yet remains to be determined due to the limited particle deposition measurement. By utilizing the CMAQv5.4 with the refined dust emission treatment (Kong et al., 2024), the East Asian dust (EAD) simulation during January 2023 was constructed to evaluate the performance of dry deposition parameterizations developed by PR11 (Pleim and Ran, 2011), E20 (Emerson et al., 2020), S22 (Shu et al., 2022) and P20 (Pleim et al., 2022), respectively. The result showed that the dry deposition parameterization could significantly improve the CMAQ dust emission treatment. By implementing the E20 dry deposition scheme, the CMAQ simulation performance of the surface PM10 has been considerably improved with the NMB of -41.9 %, as compared to the dry deposition proposed by PR11 (54.05 %), S22 (-47.01 %) and P22 (-53.90 %). The modeled PM10 pattern by E20 at the upper level (700 hPa) was mostly consistent with the observed PM10 at the Lulin Atmospheric Background Station (LABS; 23.47° N, 120.87° E; 2862 m a.s.l.) where is a typical background site at Western Pacific, particularly in capturing the peak value. The high-altitude correlations (R) were well performed for E20 by 0.55, as compared to PR11 (0.47), S22 (0.54) and P22 (0.46). Moreover, E20 improved the simulated aerosol optical depth (AOD) value during the multiple dust storm in spring 2021. The noticeable reduction of the coarse mode particle's deposition velocity (Vd) was responsible for resolving the PM10 simulation underestimation. Moreover, the significant improvement of PM10 was also shown by the modeled PM2.5 On 22–31 January 2023, the in-situ measurement of the upper level observed the possibility of natural dust and anthropogenic aerosol. This is consistent with the CMAQ, which shows that both aerosol types displayed a clear "long dust-black carbon belt" along the 15°N. We proposed implementing the E20 dry deposition approach, resolving the uncertainty of the CMAQ dust emission treatment.
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RC1: 'Comment on egusphere-2024-2549', Anonymous Referee #1, 03 Oct 2024
This paper describes a modeling study where four aerosol dry deposition schemes were used to model dust and BC. The Main point seems to be that one of the deposition schemes is best and improves the modeling of dust. This conclusion, however, is not well supported by the marginal improvement of some statistics relative to two measurements sites and MODIS AOD for brief periods during dust episodes. The problem is that the observed data is very meager and concluding that one scheme is best assumes that all other aspects of the modeling system are perfect, especially the dust emissions. Also, this a very specific application for short periods of time so there is no reason to think that these conclusions are generally relevant.
Another problem with this study is that the relative performance of the four deposition schemes is not consistent with other modeling studies. In particular, the P22 scheme typically results in significantly greater deposition velocities than the E20 scheme. Also, Fig 5 shows that P22 is almost the same as PR11. This suggests that there were errors made in running these models. Table 2 says that CMAQv5.4 was used. If the STAGE option was used for dry deposition (which should be noted in the Table) a choice of S22, E20, and P22 are available. However, PR11 is not. How was this used? Table 2 also states that the NOAH LSM was used in WRF. CMAQ needs several parameters from WRF that typically are output when using the PX LSM. When NOAH is used, default calculations for these parameters, which are important for deposition, are made in the Meteorology-Chemistry Interface Processor (MCIP). These calculations are not the same as in the LSM and will result in additional errors.
There are many grammatical and other sloppy errors in the text. Far too many for me to correct.
Specific comments
Table 1 has many errors. For example, the equations for PR11 are all for gasses not aerosols. Please remove Table 1.
Line 17. P20 should be P22.
L19. This sentence implies that dry deposition directly affects dust emissions.
L30. Sentence does not make sense.
L32-33. This sentence “resolving the uncertainty of the CMAQ dust emission treatment” is a gross overstatement.
L38. Does not make sense.
L51. Again, a gross overstatement: “Emerson et al. (2020) has resolved the problem.”
L64. What “boarder”?
L70-72. Does not make sense.
L92-93. Fix notation.
L100. Bulb?
L115-118. This is very sloppy. Please fix Vs and Vg
L122-123. This is not true: “Dry deposition is based on gravitational settling velocity (Vg), which is the function of aerodynamic and surface resistance.”
L126. Should note that STAGE is one of two options, the other being M3Dry.
L137. Here, and many other places, abbreviations such as PSEA are used without defining. Also, SDS, WPO.
L139. What are the chemical LBCs?
L156. CMAQ_Dust_PR11 is repeated.
L177. Don’t see dust claw.
L199. Table 3 should be 4.
L209. Numbers are reversed.
Fig 4. Hard to tell the different model runs apart especially for the PM25. It would help to expand the scale on the PM25 plots.
L224. Where is “the north peninsula of Southeast Asia”?
L251. There is something wrong here. P22 and PR11 should be very different.
L275-276. These results seem contrary to other modeling studies where P22 generally has greater much Vd for Accumulation mode than E20. Maybe put these numbers in a table
L286 (Fig.7). Why not show dry deposition velocity for each model rather that difference from PR11?
L300. Elemental
L330. Trans what boundary?
L350-351. The modeled BC in Fig 11h seems to end at Taiwan. Also, there is no Fig 11i.
L353. This phrase makes no sense: “ as the coarse particles could comprise of fine particles”.
L373. “vastly” is again an overstatement.
Citation: https://doi.org/10.5194/egusphere-2024-2549-RC1 -
RC2: 'Comment on egusphere-2024-2549', Anonymous Referee #2, 14 Oct 2024
This study describes an improvement to the CMAQ dry deposition over Western Pacific using various dry deposition schemes. It also addressed the performance of a model-simulated long dust-black carbon belt along 15N. The study indicated improvements in the results, but it is unclear how the improvements are statistically relevant. The impact of other processes could affect the dry deposition scheme but was not addressed. A statistical rather than a visual comparison between CMAQ and satellite/assimilated AOD would be more convincing to demonstrate modeling performances. Also, the manuscript contains numerous grammatical and technical errors that require thorough proofreading before resubmission.
Specific comments:
L 16. The abstract should not include references.
L 82. What is “LABS”?
L 115. Where is Vs in the equation?
L 168. The sentence is unclear. Clouds always induce biases in modeled and assimilated aerosols.
L 170. MERRA-2 is a data-assimilated system rather than a remotely sensed data.
L 227. MERRA-2 is a data-assimilated product rather than a pure observational product. It’s unclear how this sentence fits in with Figure 4.
Fig S1. The link in the caption does not show these synoptic maps.
Fig S2. A statistical comparison between collocated CMAQ and MODIS AOD with a scatterplot is needed to quantify their agreements.
Fig S3. A statistical comparison is also needed by using the MERRA-2 AOD as well, not just the dust column. MERRA-2 provides AOD for each species.
Citation: https://doi.org/10.5194/egusphere-2024-2549-RC2 -
RC3: 'Comment on egusphere-2024-2549', Anonymous Referee #3, 19 Oct 2024
The manuscript aims to evaluate and compare four dry deposition schemes implemented in CMAQ v5.4, focusing on simulating an East Asian dust episode from January 2023. The authors then selected the scheme by Emerson et al. (2020) (E20) for further evaluation of dust and black carbon transport.
The main issue with this work, in its current form, is that the conclusions, particularly given the strong tone used in parts of the text, are not well supported by the marginal differences between the four schemes. Specifically, the results in Table 4 and Figure 4 show small statistical significance between the models, so it's hard to justify the claim that the E20 scheme outperformed the others. Additionally, results presented in various figures seem inconsistent. For instance, Table 4 suggests a clear difference between the PR11 and P22 schemes, but Figure 5 shows minimal differences between the two (see panels d & h).
Moreover, the connection between the first part of the paper, which compares four schemes, and the second part, which focuses on dust and black carbon transport, is unclear. This makes the paper feel disjointed. The same applies to the mention of the three dust storms from 2021; it's unclear how they tie into the paper's objectives.
Overall, the manuscript appears rushed. The figures are not properly discussed, and the text contains several grammatical and stylistic errors. It would significantly improve the paper if the authors dig deeper into the mechanistic differences between the schemes and how these differences impact the simulations.
Specific Comments:
- What’s the significance of including Equations 1-4? They are all pretty standard and known to the community, and also were not referred to later in the text.
- Figure 3 is barely discussed in the text.
- Lines 380-381: The meaning here is unclear.
- Lines 369-371 and 390-391: Highly subjective statements.
- The first part of the conclusion section repeats previously discussed results.
Citation: https://doi.org/10.5194/egusphere-2024-2549-RC3
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