the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 Jan 2023
A New Look into the Impacts of Dust Radiative Forcing on the Energetics of Tropical Easterly Waves
Abstract. Saharan dust aerosols are often embedded in tropical easterly waves, also known as African easterly waves, and are transported thousands of kilometers across the tropical Atlantic Oceans, reaching the Caribbean Sea, Amazon Basin, and the eastern U.S. However, due to the complexity of the African and Atlantic climate dynamics, there is still a lack of understanding of how dust particles may influence the development of African easterly waves, which are coupled to deep convective systems over the tropical Atlantic Ocean and in some cases may seed the growth of tropical cyclones. Here we apply 22 years of daily satellite observations and reanalysis data to explore the relationships between dust in the Saharan air layer and the development of African easterly waves. Our findings show that dust aerosols are not merely transported by the African easterly jet and the African easterly waves system across the tropical Atlantic Ocean, but also contribute to the changes in the eddy energetics of the African easterly waves.
The radiative forcing efficiency of dust in the atmosphere is estimated to be a warming of approximately 20 Wm-2 over the ocean and 35 Wm-2 over land. This diabatic heating of dust aerosols in the Saharan Air Layer acts as an additional energy source to increase the growth of the waves. The enhanced diabatic heating of dust leads to the increase in meridional temperature gradients in the baroclinic zone, where eddies extract available potential energy from the mean-flow and convert it to eddy kinetic energy. This suggests that diabatic heating of dust aerosols can increase the eddy kinetic energy of the African easterly waves and enhance the baroclinicity of the region. Our findings also show that dust outbreaks over the tropical Atlantic Ocean precede the development of baroclinic waves downstream of the African easterly jet, which suggests that the dust radiative forcing has the capability to trigger the generation of the zonal and meridional transient eddies in the system comprising the African Easterly Jet and African easterly waves.
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RC1: 'Comment on egusphere-2022-1210', Anonymous Referee #1, 02 Feb 2023
Review of “A New Look into the Impacts of Dust Radiative Forcing on the Energetics of Tropical Easterly Waves” by Hosseinpour and Wilcox.
This paper explores the relationship between dust activities and the developments of the African easterly wave (AEW) system over the Atlantic Ocean. Their hypothesis is that dust aerosols enact radiative/diabatic heating, which results in an increased meridional temperature gradient in the baroclinic zone over the Atlantic. Since this zone is where “eddies extract available potential energy from the mean-flow and convert it to eddy kinetic energy,” the authors suggested that increased dust activities over the region, therefore, results in increased eddy kinetic energy (EKE) of the AEW. In addition, they showed that maximum dust radiative effect could be associated with increased EKE downstream 2-3 days later.
Because a broader understanding of the influence of African dust and the AEW system is useful to advance our understanding of the region, this study is relevant to the scientific community, and it fits into the broad scope of the journal.
While previous studies have established that aerosol radiative effect can result in changes in near-by dynamical systems, such relationships have often been shown in the absence of other confounding factors. For example, the authors cited Jones et al. 2004, who used the difference between first guess (which does not include appropriate parameterizations to account for the radiative and microphysical effects of mineral dust) and the analysis (which incorporate satellite radiance that includes dust impacts) in NCEP to estimate the impacts of dust on the AEW system. This differentiation between dust-laden and dust-free analysis is important to bring out the effects of dust on a dynamical system that is strongly coupled to its variability. Such a potential caveat to the conclusion of the analysis is not considered in this manuscript. Specifically, the author failed to also show that high values of AOD also occur when the AEW-AEJ system is strong, and therefore, the so-called “mechanistic relationship” described in the manuscript may be ascribed as a mere coincidence. Therefore, a better case of dust resulting in changes in EKE can be made if a similar signal, as described in the manuscript, results in days with high AOD but weak/low mid-tropospheric winds (e.g., AEJ). Authors should include such analysis and revise the conclusion accordingly.
Minor Comments
- 2/2 – (page/line(s)): “complexity of…..climate dynamics”?
- 2/11: here and everywhere else after this – Is it radiative “forcing” or radiative “effect”? There is a substantial difference between the two.
- 5/19: remove “the”, and say exactly the number of years you used.
- 6/2: “original version”. Is there a different version than what is publicly available? Please clarify.
- 6/12: What are these “physical properties”? Other than AOD, I don’t know what aerosol “physical properties” that are assimilated into MERRA-2. Please clarify what exactly is assimilated and why MERRA-2 is used here, instead of other reanalysis datasets.
- 6/16: Flowery language. To suggest that MERRA-2 provides the “best estimate”, you have to either reference a study for that or support your claim with evidence.
- 7/3-4: “….and Saharan dust storms are active without simultaneous transport of smoke aerosols from biomass burning as observed during the fire seasons. ….“. Are you suggesting that there is NO smoke emission from west/North Africa during the summer season at all? I believe this statement is incorrect. Also, what is the “fire season”?
- 7-8/section 2.2: Please see the comment above, radiative “forcing” is different from radiative “effect”. I believe you are referring to the radiative effect here, and perhaps everywhere else in the manuscript, and not forcing.
- 8/6: Figure numbering should start from 1 and order according to when they first appear in the manuscript.
- 8/10: Dust is not “assimilated” from the GOCART model. Please re-write this sentence, and please be accurate when you make sentences.
- 8/11: remove “best”
- 8/12: remove “the”
- 8/11-15: You do not “applied….to calculate…”, you “used….to calculate”. Please re-write this sentence.
- 8/20: Did you first average your 3-hourly data before doing the daily long-term average? Please clarify how exactly the datasets are processed for this case and every other case in your methodology.
- 9/1: “following methodology “ what methodology?
- 17/6 and 19/3: “(not shown)”. These figures should be shown in the supplementary.
- 21/19-20: Please show these boxes in Fig. 4. It appears the boxes are significantly bigger than the defined region of EKE in Fig. 4. Can you explain what determines the selected regions?
- 25/1: A direct relationship between dust and temperature gradient that connects to the baroclinicity is not made in this analysis. So why are the authors making this claim?
- 25/20: “…cause-and-effect hypothesis….” Remove “cause-and-effect “
Citation: https://doi.org/10.5194/egusphere-2022-1210-RC1 -
RC2: 'Reply on RC1', Anonymous Referee #2, 09 Feb 2023
Manuscript Summary
This study explores the relationships between dust in the Saharan air layer and the development of African easterly waves across the tropical Atlantic Ocean using 22 years of daily satellite AOD observations, as well as reanalysis MERRA-2 data based on satellite assimilation.
General Comments
Introduction:
Most references were dated. There is a lack of essential updated references in the manuscript. I found plenty of articles related to the topics described in this manuscript that were not reviewed. Here are a few examples:
- Francis et al. (2021).The dust load and radiative impact associated with the June 2020 historical Saharan dust storm. https://doi.org/10.1016/j.atmosenv.2021.118808
- Meloni et al., (2018). Determining the infrared radiative effects of Saharan dust: a radiative transfer modeling study based on vertically resolved measurements at Lampedusa. https://acp.copernicus.org/articles/18/4377/2018/
- Bercos-Hickey et al., (2017). Saharan dust and the African easterly jet–African easterly wave system: Structure, location, and energetics. https://doi.org/10.1002/qj.3128
- Konare et al., (2005). A regional climate modeling study of the effect of desert dust on the West African monsoon. https://doi.org/10.1029/2007JD009322.
- Grogan et al., (2017). Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-15-0143.1.
- Grogan et al., (2019). Structural Changes in the African Easterly Jet and Its Role in Mediating the Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-19-0104.1
- Bercos-Hickey et al., (2019). Structural Changes in the African Easterly Jet and Its Role in Mediating the Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-19-0104.1
- Francis et al. (2020). The Atmospheric Drivers of the Major Saharan Dust Storm in June 2020. https://doi.org/10.1029/2020GL090102
General Body:
- The manuscript, in its current state, has room for improvement. For example, flow, the order of the figures' numbering, and lack of tables to help the audience to understand the results the authors intend to disseminate.
- There is no discussion about their results (especially section 3 and conclusions) with updated research (For example, the above references). The manuscript needs to be improved and justified through discussions of novel peer-reviewed publications.
- The intention of using satellite data is essential. But, the co-authors need to investigate each algorithm's appropriate use more. For example, I can't entirely agree with using MERRA-2 AOD or MODIS Level 3 AOD retrievals. MERRA-2 Reanalysis and MODIS Level 3 retrievals underestimate/overestimate aerosol loading for dust and smoke. On the other hand, level 2 satellite aerosol retrievals characterize better aerosol loading. There is information in the manuscript that is not entirely correct. I encourage co-authors to investigate more about these aerosol products.
- This manuscript needs better organization. It reads disorganized and rushes in the necessary information.
Specific Comments
Introduction:
- There was no mention of the significant African aerosol components or the African dust and fire seasons.
- It should be mentioned when the Biomass and Dust season overlap.
Data and Methodology:
- While the temporal domain is stated, the spatial domain is hard to find. Also, I am unsure if the averaging method is per grid size or for the entire square domain. How many grids are contained in those squares? It would be helpful to state all those details to understand the methodology further.
- It would be helpful to create a Methodology section for data manipulation of AOD. While AOD was vaguely mentioned, unfortunately, there is no explanation of how the co-authors intended to use it. In addition, there is no information about wavelength or the retrieval collection used.
- Page 6; Lines 1-4: No relevant. Provide information just about MERRA-2.
- Page 6; Line 21: dated reference: Please update for:
- Remmer et al. (2021). The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future. https://doi.org/10.3390/rs12182900
- While MERRA-2 Reanalysis is cited, it's unclear at this point what variables were used. MERRA-2 contains multiple aerosol weather variables assimilated. It would be helpful to create a table with the variables employed in the analysis.
- Page 6; Line 22: he Deep-blue algorithm is mentioned but never cited. A few useful references:
- Sayer et al. (2019). Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land. https://doi.org/10.1029/2018JD029598.
- Hsu et al. (2019). VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long-Term Aerosol Data Records.
- Page 7: Lines 1-4. The selection of the studied period states:"… This study focuses on boreal summer months, JJA, from 2000 to 2021 because during this season, the amplitude of AEWs peaks (e.g., Roundy and Frank, 2004), and Saharan dust storms are active without simultaneous transport of smoke aerosols from biomass burning as observed during the fire seasons…." I suggest all co-authors study the NASA ORACLES campaign.
- Redemann et al., (2020). An overview of the ORACLES (ObseRvations of Aerosols above Clouds and their intEractionS) project aerosol–cloud–radiation interactions in the southeast Atlantic basin. https://acp.copernicus.org/articles/21/1507/2021/
- Cochrane et al., (2019). Above-cloud aerosol radiative effects based on ORACLES 2016 and ORACLES 2017 aircraft experiments. https://amt.copernicus.org/articles/12/6505/2019/
- Cochrane et al., (2021). Biomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above Clouds and their intEractionS) 2016 and 2017 experiments. https://amt.copernicus.org/articles/15/61/2022/
- I am skeptical that in 20 years of the study, the atmosphere would not have a mix of smoke and dust on specific episodes. But unfortunately, there is no methodology from the co-authors to warranty the presence of dust.
- Page 8: Line 6. It would be helpful to the reader to start refereeing the figures in order. For example, referencing Figure 2 confused me and made me go back several times to ensure I did not miss Figure 1.
- Section 2.3: The weather variables used in this study were finally introduced here. However, this format is very disorganized because this section supposes to be about the calculation of MKE instead of introducing MERRA-2 variables or algorithms.
- Page 8: Lines 9-11. The introduction of GOCART should not have been explained in this section, which is about the formulation of MKE.
- Randles et al. (2017). The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation. https://journals.ametsoc.org/view/journals/clim/30/17/jcli-d-16-0609.1.xml
- Goddard Chemistry, Aerosol, Radiation, and Transport model (GOCART)
- For sections 2.3, 2.4, and 2.5, are the averages per grid cell or for the entire domain?
Summary of the results
- Page 17. Lines 1-9. Deep-blue has an ocean retrieval for Levels 2 and 3 data and for VIIRS. Please, edit accordingly. This would not be a challenge using level 2 data for this manuscript. Check page 127
https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_ATBD_C6_C61_2019_02_20.pdf
- Page 17. Line 17: How did you calculate aerosol shortwave radiative forcing from the MERRA-2? It would be nice to reference Eq. 1
- Have you compared MERRA-2 AOD with the satellite data? While correlation factors are high and p values are low, the magnitude in the color bars and gradients of the data in the maps are different. I want to remind co-authors that two datasets can have high correlation factors with high biases. My concerns are related to the ocean gradient specifically.
- Page 19. Lines 1-3. I encourage you to show these results in an appendix.
- Section 3.3 states previous studies have discussed the development of the AEWs, but I did not find any reference or comparison to other studies in sections 3.3.1 and 3.3.2.
Conclusions
Conclusions in this manuscript are not reinforced by any peer-review publication.
Data availability
Page 26. Line 9: Use MODIS AOD retrievals instead of observations. This study did not use direct observations from MODIS.
Figures
Figure 2.a. Did you mean MODIS Dark-Target AOD (550 nm) ? Did you use 500 nm instead of 550 nm?
https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_ATBD_C6_C61_2019_02_20.pdf
Figure 2.b. Did you mean MODIS Deep-Blue AOD (550 nm). I encourage consistency in figs 2 a and b.
- AC1: 'Comment on egusphere-2022-1210', Farnaz Hosseinpour, 26 Apr 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1210', Anonymous Referee #1, 02 Feb 2023
Review of “A New Look into the Impacts of Dust Radiative Forcing on the Energetics of Tropical Easterly Waves” by Hosseinpour and Wilcox.
This paper explores the relationship between dust activities and the developments of the African easterly wave (AEW) system over the Atlantic Ocean. Their hypothesis is that dust aerosols enact radiative/diabatic heating, which results in an increased meridional temperature gradient in the baroclinic zone over the Atlantic. Since this zone is where “eddies extract available potential energy from the mean-flow and convert it to eddy kinetic energy,” the authors suggested that increased dust activities over the region, therefore, results in increased eddy kinetic energy (EKE) of the AEW. In addition, they showed that maximum dust radiative effect could be associated with increased EKE downstream 2-3 days later.
Because a broader understanding of the influence of African dust and the AEW system is useful to advance our understanding of the region, this study is relevant to the scientific community, and it fits into the broad scope of the journal.
While previous studies have established that aerosol radiative effect can result in changes in near-by dynamical systems, such relationships have often been shown in the absence of other confounding factors. For example, the authors cited Jones et al. 2004, who used the difference between first guess (which does not include appropriate parameterizations to account for the radiative and microphysical effects of mineral dust) and the analysis (which incorporate satellite radiance that includes dust impacts) in NCEP to estimate the impacts of dust on the AEW system. This differentiation between dust-laden and dust-free analysis is important to bring out the effects of dust on a dynamical system that is strongly coupled to its variability. Such a potential caveat to the conclusion of the analysis is not considered in this manuscript. Specifically, the author failed to also show that high values of AOD also occur when the AEW-AEJ system is strong, and therefore, the so-called “mechanistic relationship” described in the manuscript may be ascribed as a mere coincidence. Therefore, a better case of dust resulting in changes in EKE can be made if a similar signal, as described in the manuscript, results in days with high AOD but weak/low mid-tropospheric winds (e.g., AEJ). Authors should include such analysis and revise the conclusion accordingly.
Minor Comments
- 2/2 – (page/line(s)): “complexity of…..climate dynamics”?
- 2/11: here and everywhere else after this – Is it radiative “forcing” or radiative “effect”? There is a substantial difference between the two.
- 5/19: remove “the”, and say exactly the number of years you used.
- 6/2: “original version”. Is there a different version than what is publicly available? Please clarify.
- 6/12: What are these “physical properties”? Other than AOD, I don’t know what aerosol “physical properties” that are assimilated into MERRA-2. Please clarify what exactly is assimilated and why MERRA-2 is used here, instead of other reanalysis datasets.
- 6/16: Flowery language. To suggest that MERRA-2 provides the “best estimate”, you have to either reference a study for that or support your claim with evidence.
- 7/3-4: “….and Saharan dust storms are active without simultaneous transport of smoke aerosols from biomass burning as observed during the fire seasons. ….“. Are you suggesting that there is NO smoke emission from west/North Africa during the summer season at all? I believe this statement is incorrect. Also, what is the “fire season”?
- 7-8/section 2.2: Please see the comment above, radiative “forcing” is different from radiative “effect”. I believe you are referring to the radiative effect here, and perhaps everywhere else in the manuscript, and not forcing.
- 8/6: Figure numbering should start from 1 and order according to when they first appear in the manuscript.
- 8/10: Dust is not “assimilated” from the GOCART model. Please re-write this sentence, and please be accurate when you make sentences.
- 8/11: remove “best”
- 8/12: remove “the”
- 8/11-15: You do not “applied….to calculate…”, you “used….to calculate”. Please re-write this sentence.
- 8/20: Did you first average your 3-hourly data before doing the daily long-term average? Please clarify how exactly the datasets are processed for this case and every other case in your methodology.
- 9/1: “following methodology “ what methodology?
- 17/6 and 19/3: “(not shown)”. These figures should be shown in the supplementary.
- 21/19-20: Please show these boxes in Fig. 4. It appears the boxes are significantly bigger than the defined region of EKE in Fig. 4. Can you explain what determines the selected regions?
- 25/1: A direct relationship between dust and temperature gradient that connects to the baroclinicity is not made in this analysis. So why are the authors making this claim?
- 25/20: “…cause-and-effect hypothesis….” Remove “cause-and-effect “
Citation: https://doi.org/10.5194/egusphere-2022-1210-RC1 -
RC2: 'Reply on RC1', Anonymous Referee #2, 09 Feb 2023
Manuscript Summary
This study explores the relationships between dust in the Saharan air layer and the development of African easterly waves across the tropical Atlantic Ocean using 22 years of daily satellite AOD observations, as well as reanalysis MERRA-2 data based on satellite assimilation.
General Comments
Introduction:
Most references were dated. There is a lack of essential updated references in the manuscript. I found plenty of articles related to the topics described in this manuscript that were not reviewed. Here are a few examples:
- Francis et al. (2021).The dust load and radiative impact associated with the June 2020 historical Saharan dust storm. https://doi.org/10.1016/j.atmosenv.2021.118808
- Meloni et al., (2018). Determining the infrared radiative effects of Saharan dust: a radiative transfer modeling study based on vertically resolved measurements at Lampedusa. https://acp.copernicus.org/articles/18/4377/2018/
- Bercos-Hickey et al., (2017). Saharan dust and the African easterly jet–African easterly wave system: Structure, location, and energetics. https://doi.org/10.1002/qj.3128
- Konare et al., (2005). A regional climate modeling study of the effect of desert dust on the West African monsoon. https://doi.org/10.1029/2007JD009322.
- Grogan et al., (2017). Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-15-0143.1.
- Grogan et al., (2019). Structural Changes in the African Easterly Jet and Its Role in Mediating the Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-19-0104.1
- Bercos-Hickey et al., (2019). Structural Changes in the African Easterly Jet and Its Role in Mediating the Effects of Saharan Dust on the Linear Dynamics of African Easterly Waves. https://doi.org/10.1175/JAS-D-19-0104.1
- Francis et al. (2020). The Atmospheric Drivers of the Major Saharan Dust Storm in June 2020. https://doi.org/10.1029/2020GL090102
General Body:
- The manuscript, in its current state, has room for improvement. For example, flow, the order of the figures' numbering, and lack of tables to help the audience to understand the results the authors intend to disseminate.
- There is no discussion about their results (especially section 3 and conclusions) with updated research (For example, the above references). The manuscript needs to be improved and justified through discussions of novel peer-reviewed publications.
- The intention of using satellite data is essential. But, the co-authors need to investigate each algorithm's appropriate use more. For example, I can't entirely agree with using MERRA-2 AOD or MODIS Level 3 AOD retrievals. MERRA-2 Reanalysis and MODIS Level 3 retrievals underestimate/overestimate aerosol loading for dust and smoke. On the other hand, level 2 satellite aerosol retrievals characterize better aerosol loading. There is information in the manuscript that is not entirely correct. I encourage co-authors to investigate more about these aerosol products.
- This manuscript needs better organization. It reads disorganized and rushes in the necessary information.
Specific Comments
Introduction:
- There was no mention of the significant African aerosol components or the African dust and fire seasons.
- It should be mentioned when the Biomass and Dust season overlap.
Data and Methodology:
- While the temporal domain is stated, the spatial domain is hard to find. Also, I am unsure if the averaging method is per grid size or for the entire square domain. How many grids are contained in those squares? It would be helpful to state all those details to understand the methodology further.
- It would be helpful to create a Methodology section for data manipulation of AOD. While AOD was vaguely mentioned, unfortunately, there is no explanation of how the co-authors intended to use it. In addition, there is no information about wavelength or the retrieval collection used.
- Page 6; Lines 1-4: No relevant. Provide information just about MERRA-2.
- Page 6; Line 21: dated reference: Please update for:
- Remmer et al. (2021). The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future. https://doi.org/10.3390/rs12182900
- While MERRA-2 Reanalysis is cited, it's unclear at this point what variables were used. MERRA-2 contains multiple aerosol weather variables assimilated. It would be helpful to create a table with the variables employed in the analysis.
- Page 6; Line 22: he Deep-blue algorithm is mentioned but never cited. A few useful references:
- Sayer et al. (2019). Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land. https://doi.org/10.1029/2018JD029598.
- Hsu et al. (2019). VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long-Term Aerosol Data Records.
- Page 7: Lines 1-4. The selection of the studied period states:"… This study focuses on boreal summer months, JJA, from 2000 to 2021 because during this season, the amplitude of AEWs peaks (e.g., Roundy and Frank, 2004), and Saharan dust storms are active without simultaneous transport of smoke aerosols from biomass burning as observed during the fire seasons…." I suggest all co-authors study the NASA ORACLES campaign.
- Redemann et al., (2020). An overview of the ORACLES (ObseRvations of Aerosols above Clouds and their intEractionS) project aerosol–cloud–radiation interactions in the southeast Atlantic basin. https://acp.copernicus.org/articles/21/1507/2021/
- Cochrane et al., (2019). Above-cloud aerosol radiative effects based on ORACLES 2016 and ORACLES 2017 aircraft experiments. https://amt.copernicus.org/articles/12/6505/2019/
- Cochrane et al., (2021). Biomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above Clouds and their intEractionS) 2016 and 2017 experiments. https://amt.copernicus.org/articles/15/61/2022/
- I am skeptical that in 20 years of the study, the atmosphere would not have a mix of smoke and dust on specific episodes. But unfortunately, there is no methodology from the co-authors to warranty the presence of dust.
- Page 8: Line 6. It would be helpful to the reader to start refereeing the figures in order. For example, referencing Figure 2 confused me and made me go back several times to ensure I did not miss Figure 1.
- Section 2.3: The weather variables used in this study were finally introduced here. However, this format is very disorganized because this section supposes to be about the calculation of MKE instead of introducing MERRA-2 variables or algorithms.
- Page 8: Lines 9-11. The introduction of GOCART should not have been explained in this section, which is about the formulation of MKE.
- Randles et al. (2017). The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation. https://journals.ametsoc.org/view/journals/clim/30/17/jcli-d-16-0609.1.xml
- Goddard Chemistry, Aerosol, Radiation, and Transport model (GOCART)
- For sections 2.3, 2.4, and 2.5, are the averages per grid cell or for the entire domain?
Summary of the results
- Page 17. Lines 1-9. Deep-blue has an ocean retrieval for Levels 2 and 3 data and for VIIRS. Please, edit accordingly. This would not be a challenge using level 2 data for this manuscript. Check page 127
https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_ATBD_C6_C61_2019_02_20.pdf
- Page 17. Line 17: How did you calculate aerosol shortwave radiative forcing from the MERRA-2? It would be nice to reference Eq. 1
- Have you compared MERRA-2 AOD with the satellite data? While correlation factors are high and p values are low, the magnitude in the color bars and gradients of the data in the maps are different. I want to remind co-authors that two datasets can have high correlation factors with high biases. My concerns are related to the ocean gradient specifically.
- Page 19. Lines 1-3. I encourage you to show these results in an appendix.
- Section 3.3 states previous studies have discussed the development of the AEWs, but I did not find any reference or comparison to other studies in sections 3.3.1 and 3.3.2.
Conclusions
Conclusions in this manuscript are not reinforced by any peer-review publication.
Data availability
Page 26. Line 9: Use MODIS AOD retrievals instead of observations. This study did not use direct observations from MODIS.
Figures
Figure 2.a. Did you mean MODIS Dark-Target AOD (550 nm) ? Did you use 500 nm instead of 550 nm?
https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_ATBD_C6_C61_2019_02_20.pdf
Figure 2.b. Did you mean MODIS Deep-Blue AOD (550 nm). I encourage consistency in figs 2 a and b.
- AC1: 'Comment on egusphere-2022-1210', Farnaz Hosseinpour, 26 Apr 2023
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Eric M. Wilcox
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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