the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Dec 2023
A revised parameterization for aerosol, cloud and precipitation pH for use in chemical forecasting systems (EQSAM4Clim-v12)
Abstract. The Equilibrium Simplified Aerosol Model for Climate version 12 (EQSAM4Clim-v12) has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. EQSAM4Clim is based on an analytical concept that is not only sufficiently fast for numerical weather prediction (NWP) applications, but also free of numerical noise, which makes it attractive also for air quality forecasting. EQSAM4Clim allows the calculation of aerosol composition based on the gas-liquid-solid and the reduced gas-liquid partitioning with the associated water uptake for both cases, and can therefore provide important information about the acidity of the aerosols. Here we provide a comprehensive description of the recent changes made to the aerosol acidity parameterization (referred to a version 12) which builds on the original EQSAM4Clim. We evaluate the pH improvements using a detailed box-model and compare against previous model calculations and both ground-based and aircraft observations from US and China covering different seasons and scenarios. We show that, in most cases, the simulated pH is within reasonable agreement with the results of the E-AIM reference model and of satisfactory accuracy.
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Notice on discussion status
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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Preprint
(2932 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2932 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2930, better title?', Anonymous Referee #1, 15 Jan 2024
General comments
The paper presents another important evaluation for the efficient thermodynamic and chemical aerosol model EQSAM including some additional information on parameterizations and an application. This should be reflected more clearly in the title. EQSAM can be used as module in global and regional models or forecasting systems which should be mentioned explicitly in the introduction. The manuscript might be published after minor revision.
Specific comments
Line 96: This sentence has to be improved for clarity. Does this mean a total factor of 100 in case D3? The use of 'N' together with 'XN' is also confusing, better use another letter (or 'Xn').
Line 159: "including E-AIM" should be inserted after "models" for better understanding the following.
Lines 167-177: This can be expressed in a shorter way.
Line 234: Refer also to Fig 7b and say that V10 is worse here.
Technical corrections
Line 10: Define acronym, line 44 is too late.
Line 13: The acronym is already defined in abstract.
Line 16: Define acronym IFS, line 28 too late.
Line 17: Has the accompanying paper a reference? Or the references in lines 27, 243f? Define acronym.
Line 25: Acronym already defined in abstract.
Line 74: Define also Z* and H+* here (missing for Eqn.5).
Line 84: Parentheses messed up.
Line 91: Typo
Lines 117 and 144: Remove the repetitions of the definitions in line 109f.
Line 166ff: This punctuation is confusing, use ',' instead of '-' between species and '+' instead of '/' as in caption of Fig. 2.
Figure 2 to 6: It would be better to use actual time as abscissa than the data point number (as Fig. 8). The additional title near the abscissa of panel d should be removed and might appear in caption.
Figure 8: Don't mess up different notations for time at abscissa (dd/mm/yy and mm.dd.yyyy.hh).
Line 243: Typo.Citation: https://doi.org/10.5194/egusphere-2023-2930-RC1 -
AC1: 'Reply on RC1', Swen Metzger, 05 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2930/egusphere-2023-2930-AC1-supplement.pdf
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AC1: 'Reply on RC1', Swen Metzger, 05 Mar 2024
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RC2: 'Comment on egusphere-2023-2930', Anonymous Referee #2, 23 Jan 2024
The Technical Note presents an updated version of EQSAM, i.e. EQSAM4Clim-v12, which has been improved to simulate a more accurate pH of aerosol associated water (AW), and also in cloud water and precipitation. Accurate, numerically robust and efficient schemes to calculate the gas/aerosol partitioning, aerosol water and pH are indeed in large demand by regional and global chemical transport models (CTM) for both air quality assessments and forecasts. My recommendation is that the paper can be published in EGUsphere after minor revisions.
General comments:
I do not understand why it’s stressed that the EQSAM4Clim-v12 is primarily meant for “chemical forecasting systems”. It can indeed be implemented in any CTM used for Chemical Weather prediction and Air quality simulations, but also in climate models.
Then, I’d recommend to include in the relevant sections:
- brief explanation of the need/importance of modelling aerosol water pH
- more clear outline of the improvements introduced with respect to the previous version and what particular processes and results (in what particular cases) they improved (was it only the factor XN, line 91?)
- what tests have been performed to check that the scheme is “free for numerical noise” (lines 4, 38, 57)
- with respect to the EQSAM4Clim-v12 being (sufficiently) accurate, it’d be helpful to also outline the cases/conditions when it is less accurate (e.g. specific aerosol compositions, regimes, and probably for very high RH, see Specific comments)
- Regarding high RH, the values as high as 98-99 and even 100% from weather prediction models can be in the meteorological inputs to CTMs. Such cases do not seem to be considered in this note. I think that a very clear recommendation should be made (actually it’d be very important) on the applicability of the parameterization
- it’d be useful to summarize for which of the cases the discrepancies between EQSAM4Clim-v12 and E-AIM are largest/smallest (more/less acid, more/less complex chemical system). And thus, how could this affect the results in CTMs with less complex chemical systems (e.g. missing some of base cations)?
Specific comments (referred to the line numbers):
Section 2.2.1 lines 96-103: could you better explain where those “correction factors” come from; how the values were found
Is LWC_equilib (eq. 9a and l. 139) the same as AW?
146-147: could you outline the main implications of not using pH and H+ in EQSAM
151: Sounds a bit strange to recommend E-AIM for “accurate pH calculations” after it’s been declared that EQSAM4Clim-v12 is “accurate/sufficiently accurate”. Maybe to specify what calculations/applications/particular cases etc the authors mean here.
152-153: please list the known to the authors limitations for the parameterisation, the cases when it’s not applicable
180-183: Explain more transparently the correction factors. Are those general or valid only for the considered cases? In the latter case, how should they be derived for new application cases?
190-191: and elsewhere: explain what should be expected at RH approaching 100%
218-220: “different aerosol compositions…” - different from what? Or if different between them, what’s the connection to the “most differing results”?
264: what about less complex aerosol cases?
Technical revisions:
3: Probably should be “chemical weather prediction”
7: (referred to as a version…)
59: oxidation products of emissions from natural sources and …
62: add i.e. or “namely before listing the cations
91: should be “dependent”
106, 108: remove redundant “)”
117-118 and 144 - repetitive explanations for LWC0 and molality0 (already given on L. 109-110)
156 : “which also was used” instead of “where this data has been used”
159: in chemical transport models? (large scale)
164: sorted by decreasing? Complexity
178-179: please add the upper range RH value (above 20% and up to XX % RH)
185-186: repetition200: Suggestion: These results show similar variability of AW content…
217, 223: What are those (a) and (b) for?
217: I’d say “the pH results differ the most for Cabauw”
218-220: the sentence seems incomplete. Probably it should be merged with the next one.
Section 3.2: I think it would make more sense to at least compare IFS with 3h averages from the box models to reduce at least a bit the inconsistency. Why are there several gaps in the box model results?
257: Suggestion: regional and global chemical transport models.
Citation: https://doi.org/10.5194/egusphere-2023-2930-RC2 -
AC2: 'Reply on RC2', Swen Metzger, 05 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2930/egusphere-2023-2930-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Swen Metzger, 05 Mar 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2930, better title?', Anonymous Referee #1, 15 Jan 2024
General comments
The paper presents another important evaluation for the efficient thermodynamic and chemical aerosol model EQSAM including some additional information on parameterizations and an application. This should be reflected more clearly in the title. EQSAM can be used as module in global and regional models or forecasting systems which should be mentioned explicitly in the introduction. The manuscript might be published after minor revision.
Specific comments
Line 96: This sentence has to be improved for clarity. Does this mean a total factor of 100 in case D3? The use of 'N' together with 'XN' is also confusing, better use another letter (or 'Xn').
Line 159: "including E-AIM" should be inserted after "models" for better understanding the following.
Lines 167-177: This can be expressed in a shorter way.
Line 234: Refer also to Fig 7b and say that V10 is worse here.
Technical corrections
Line 10: Define acronym, line 44 is too late.
Line 13: The acronym is already defined in abstract.
Line 16: Define acronym IFS, line 28 too late.
Line 17: Has the accompanying paper a reference? Or the references in lines 27, 243f? Define acronym.
Line 25: Acronym already defined in abstract.
Line 74: Define also Z* and H+* here (missing for Eqn.5).
Line 84: Parentheses messed up.
Line 91: Typo
Lines 117 and 144: Remove the repetitions of the definitions in line 109f.
Line 166ff: This punctuation is confusing, use ',' instead of '-' between species and '+' instead of '/' as in caption of Fig. 2.
Figure 2 to 6: It would be better to use actual time as abscissa than the data point number (as Fig. 8). The additional title near the abscissa of panel d should be removed and might appear in caption.
Figure 8: Don't mess up different notations for time at abscissa (dd/mm/yy and mm.dd.yyyy.hh).
Line 243: Typo.Citation: https://doi.org/10.5194/egusphere-2023-2930-RC1 -
AC1: 'Reply on RC1', Swen Metzger, 05 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2930/egusphere-2023-2930-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Swen Metzger, 05 Mar 2024
-
RC2: 'Comment on egusphere-2023-2930', Anonymous Referee #2, 23 Jan 2024
The Technical Note presents an updated version of EQSAM, i.e. EQSAM4Clim-v12, which has been improved to simulate a more accurate pH of aerosol associated water (AW), and also in cloud water and precipitation. Accurate, numerically robust and efficient schemes to calculate the gas/aerosol partitioning, aerosol water and pH are indeed in large demand by regional and global chemical transport models (CTM) for both air quality assessments and forecasts. My recommendation is that the paper can be published in EGUsphere after minor revisions.
General comments:
I do not understand why it’s stressed that the EQSAM4Clim-v12 is primarily meant for “chemical forecasting systems”. It can indeed be implemented in any CTM used for Chemical Weather prediction and Air quality simulations, but also in climate models.
Then, I’d recommend to include in the relevant sections:
- brief explanation of the need/importance of modelling aerosol water pH
- more clear outline of the improvements introduced with respect to the previous version and what particular processes and results (in what particular cases) they improved (was it only the factor XN, line 91?)
- what tests have been performed to check that the scheme is “free for numerical noise” (lines 4, 38, 57)
- with respect to the EQSAM4Clim-v12 being (sufficiently) accurate, it’d be helpful to also outline the cases/conditions when it is less accurate (e.g. specific aerosol compositions, regimes, and probably for very high RH, see Specific comments)
- Regarding high RH, the values as high as 98-99 and even 100% from weather prediction models can be in the meteorological inputs to CTMs. Such cases do not seem to be considered in this note. I think that a very clear recommendation should be made (actually it’d be very important) on the applicability of the parameterization
- it’d be useful to summarize for which of the cases the discrepancies between EQSAM4Clim-v12 and E-AIM are largest/smallest (more/less acid, more/less complex chemical system). And thus, how could this affect the results in CTMs with less complex chemical systems (e.g. missing some of base cations)?
Specific comments (referred to the line numbers):
Section 2.2.1 lines 96-103: could you better explain where those “correction factors” come from; how the values were found
Is LWC_equilib (eq. 9a and l. 139) the same as AW?
146-147: could you outline the main implications of not using pH and H+ in EQSAM
151: Sounds a bit strange to recommend E-AIM for “accurate pH calculations” after it’s been declared that EQSAM4Clim-v12 is “accurate/sufficiently accurate”. Maybe to specify what calculations/applications/particular cases etc the authors mean here.
152-153: please list the known to the authors limitations for the parameterisation, the cases when it’s not applicable
180-183: Explain more transparently the correction factors. Are those general or valid only for the considered cases? In the latter case, how should they be derived for new application cases?
190-191: and elsewhere: explain what should be expected at RH approaching 100%
218-220: “different aerosol compositions…” - different from what? Or if different between them, what’s the connection to the “most differing results”?
264: what about less complex aerosol cases?
Technical revisions:
3: Probably should be “chemical weather prediction”
7: (referred to as a version…)
59: oxidation products of emissions from natural sources and …
62: add i.e. or “namely before listing the cations
91: should be “dependent”
106, 108: remove redundant “)”
117-118 and 144 - repetitive explanations for LWC0 and molality0 (already given on L. 109-110)
156 : “which also was used” instead of “where this data has been used”
159: in chemical transport models? (large scale)
164: sorted by decreasing? Complexity
178-179: please add the upper range RH value (above 20% and up to XX % RH)
185-186: repetition200: Suggestion: These results show similar variability of AW content…
217, 223: What are those (a) and (b) for?
217: I’d say “the pH results differ the most for Cabauw”
218-220: the sentence seems incomplete. Probably it should be merged with the next one.
Section 3.2: I think it would make more sense to at least compare IFS with 3h averages from the box models to reduce at least a bit the inconsistency. Why are there several gaps in the box model results?
257: Suggestion: regional and global chemical transport models.
Citation: https://doi.org/10.5194/egusphere-2023-2930-RC2 -
AC2: 'Reply on RC2', Swen Metzger, 05 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2930/egusphere-2023-2930-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Swen Metzger, 05 Mar 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
The EQSAM Box Model (for eqsam4clim-v12) Swen Metzger https://doi.org/10.5281/zenodo.10276178
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Samuel Rémy
Jason E. Williams
Vincent Huijnen
Johannes Flemming
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2932 KB) - Metadata XML