the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Combining Regional Mesh Refinement With Vertically Enhanced Physics to Target Marine Stratocumulus Biases
- 1Lawrence Livermore National Laboratory, Livermore, CA, USA
- 2Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
- 3NOAA Earth System Research Laboratories, Chemical Science Laboratory, Boulder, CO, USA
- 1Lawrence Livermore National Laboratory, Livermore, CA, USA
- 2Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
- 3NOAA Earth System Research Laboratories, Chemical Science Laboratory, Boulder, CO, USA
Abstract. In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement of Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the Southeast Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the longstanding biases associated with marine stratocmulus in GCMs when compared to the standard resolution control simulation.
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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
(22315 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.
Journal article(s) based on this preprint
Peter A. Bogenschutz et al.
Interactive discussion
Status: closed
-
CEC1: 'Comment on gmd-2022-175', Astrid Kerkweg, 18 Aug 2022
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
So E3SM-FIVE including a version number / identifier should be added to the title of the article. Please add this change when submitting the revised version of the manuscript.
Additionally, the GMD editorial states about Model experiment description papers: "The primary purpose of these papers is to enable modelling communities to perform the same experiments. Therefore, everything required to run the experiment must be provided, apart from the model itself." (GMD Editorial main text, see also appendix B4)
I do not see that your article is about a model experiment which is performed by a larger community with different models. Therefore, your paper fits better the "Technical and development paper" type and I will ask the editorial office to apply this type to your article.
Yours, Astrid Kerkweg
- AC1: 'Reply on CEC1', Peter Bogenschutz, 21 Nov 2022
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RC1: 'Comment on gmd-2022-175', Anonymous Referee #1, 20 Sep 2022
Bogenschutz et al. have presented a novel GCM framework that combines regional mesh refinement with vertically enhanced physics to improve simulated marine stratocumulus. The study addresses advancement in GCM and cloud modeling, which is well within the scope of GMD. Although previous studies have explored and documented the performance of regional mesh refinement and vertically enhanced physics separately in GCMs, the combination of the two is new. Therefore, this study presents a sufficiently substantial advance in modeling science. The paper is clearly written, well structured, and easy to follow. The conclusion, mainly that their novel framework can reproduce high resolution benchmark simulation with substantially lower computational cost, is well supported by the results.
I only have a few comments below:
L195-200: How is “low level cloud” defined?
L230-235: Presumably, Figure 5b shows the global impact of reduced SEP Sc bias. For example, it shows an increased low cloud amount along the ITCZ. Although it is not within the scope of this paper to discuss the global impact of reduced Sc bias, it would be helpful to provide information on whether the differences we see on Figure 5 are significant. This can help guide future work.
L290: In general, I would like to see more discussion on the mechanisms behind the improvement in SEP-RRM-FIVE. What processes lead to improved Sc with FIVE and with RRM respectively? Here the authors touched on turbulence and cloud top feedback. More detailed discussion would be appreciated.
L315-320: The presence of positive and negative bias along the coast in DJF, MMA, and SON in FIVE simulations suggests that the location of the Sc deck is shifted north of the observed Sc. Is this the case? If so, does it suggest that the bias is related to large-scale circulation instead of BL processes?
L330: “further refinement of the vertical grid in VEP could lead to additional improvements”, are there studies to support this claim?
-
AC2: 'Reply on RC1', Peter Bogenschutz, 21 Nov 2022
We thank Reviewer 1 for their time, comments, and helping to make this a better manuscript. Please see our reply to each comment below. For exact wording changes and additions made to the manuscript, please refer to the marked up manuscript.
Reviewer Comment: L195-200: How is “low level cloud” defined?
Response: Text has been added in the second paragraph of section 4.1 to address this and with reference given for the LIDAR retrieval.
Reviewer Comment: L230-235: Presumably, Figure 5b shows the global impact of reduced SEP Sc bias. For example, it shows an increased low cloud amount along the ITCZ. Although it is not within the scope of this paper to discuss the global impact of reduced Sc bias, it would be helpful to provide information on whether the differences we see on Figure 5 are significant. This can help guide future work.
Response: This is an excellent suggestion! We have added stippled areas to this plot to show where differences are statistically significant. In addition, text was modified/added in section 4.1 to discuss these results.
Reviewer Comment: L290: In general, I would like to see more discussion on the mechanisms behind the improvement in SEP-RRM-FIVE. What processes lead to improved Sc with FIVE and with RRM respectively? Here the authors touched on turbulence and cloud top feedback. More detailed discussion would be appreciated.
Response: Thank you for this suggestion. Yes, we agree more description and context was needed. At the end of section 4.1 we added a couple paragraphs to address this.
Reviewer Comment: L315-320: The presence of positive and negative bias along the coast in DJF, MMA, and SON in FIVE simulations suggests that the location of the Sc deck is shifted north of the observed Sc. Is this the case? If so, does it suggest that the bias is related to large-scale circulation instead of BL processes?
Response: This is a very interesting point and thus far our analysis has not shown strong evidence that the errors in the large-scale circulation are the leading cause of this placement bias. We hypothesize that parameterization deficiencies are the first order cause of the remaining bias, as already noted in the text.
Reviewer Comment: L330: “further refinement of the vertical grid in VEP could lead to additional improvements”, are there studies to support this claim?
Response: It was found in the original E3SM-FIVE prototype paper (Lee et al. 2021) that running with increased vertical resolution (16x relative to E3SM in the boundary layer) beyond that used in this paper (8x) has modest improvements to the Sc biases. Thus, It is possible that 16x vertical resolution in FIVE coupled with high horizontal resolution could further reduce the biases presented in this paper. The appropriate reference has been added near original line L330 (at the end of section 4.2) to support our speculation.
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AC2: 'Reply on RC1', Peter Bogenschutz, 21 Nov 2022
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RC2: 'Comment on gmd-2022-175', Anonymous Referee #2, 01 Nov 2022
Combining Regional Mesh RefinementWith Vertically Enhanced Physics to Target Marine Stratocumulus Biases
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
This study investigates the ability of improving the simulation of marine stratocumulus by modifying the vertical and horizontal resolutions. Since low clouds are more realistic in global high-resolution simulations, the authors test whether improving only the vertical resolution and /or locally refining the horizontal grid can reproduce this improvement. If so, this would lead to have better simulations with a relatively lower computational cost increase.
For that purpose, the authors analyze 6 global simulations: low, regionally-high, and high horizontal resolution, with and without high vertical resolutions (only for selected processes). They find that, firstly, having a finer vertical resolution for the parameterized processes, and secondly, refining the horizontal grid in the region of interest, significantly improves the simulation of marine stratocumulus (cloud amount and radiative effects). The authors conclude by advocating the usefulness of their framework for process-oriented analysis and sensitivity tests.
I find the article interesting and well written. The lack of improvement in representing stratocumulus and other boundary-layer clouds remains challenging. Therefore, the focus of the paper is of particular interest. Given the rise of global high-resolution modeling, it is important to provide insight into the effectiveness of improving low clouds with refined resolutions. However, I don't really understand how this happens. Using FIVE, some parameterized processes should be better represented, but it is not explained which of them mostly explains this difference, and how the changes act on the cloud coverage. Is it related to the way some processes are represented at the sub-grid scale and are sensitive to resolution (e.g. scale awareness)? Is it cloud-top entrainment, convective transport, turbulence closure, cloud radiation? This would help clarify why resolutions are so important, and how other climate modeling groups might use this framework.
So I thus suggest that the article be accepted after the minor comments I highlight. I would like to see the authors describe in more detail the reasons why vertical resolution is so important, and which processes are most sensitive to this refinement.
Specific comments:
- Line 59: "panacea": Unclear and not necessary.
- Line 100: "elements": Unclear. Do you mean grid boxes/columns?
- Lines 283-285 + Figure 6b: How do you explain that the RMSE is as high in the HR simulations as in LR? Does this suggest that HR simulations are not realistic in reproducing spatial pattern of low clouds?
- The variability of the COSP low-cloud amount may differ from the model cloud variability by changes in the high-cloud amount. How much does this influence the biases in the seasonal variability (Figure 12)? Overall, do the authors find the same result (improvement by FIVE, and HR) if using the model low-cloud amount?
- Line 370-371: What is the relative coverage of the SEP-RRM region? This would be a relevant comparison to the 0.05% the authors put forward.
-
AC3: 'Reply on RC2', Peter Bogenschutz, 21 Nov 2022
We thank Reviewer 2 for their time, comments, and helping to make this a better manuscript. Please see our reply to each comment below. For exact wording changes and additions made to the manuscript, please refer to the marked up manuscript.
Reviewer Comment: I find the article interesting and well written. The lack of improvement in representing stratocumulus and other boundary-layer clouds remains challenging. Therefore, the focus of the paper is of particular interest. Given the rise of global high-resolution modeling, it is important to provide insight into the effectiveness of improving low clouds with refined resolutions. However, I don't really understand how this happens. Using FIVE, some parameterized processes should be better represented, but it is not explained which of them mostly explains this difference, and how the changes act on the cloud coverage. Is it related to the way some processes are represented at the sub-grid scale and are sensitive to resolution (e.g. scale awareness)? Is it cloud-top entrainment, convective transport, turbulence closure, cloud radiation? This would help clarify why resolutions are so important, and how other climate modeling groups might use this framework.
So I thus suggest that the article be accepted after the minor comments I highlight. I would like to see the authors describe in more detail the reasons why vertical resolution is so important, and which processes are most sensitive to this refinement.
Response: Thank you for this excellent suggestion. Yes, we agree more description and context was needed. At the end of section 4.1 we added a couple paragraphs to address this.
Specific comments:
Reviewer Comment: Line 59: "panacea": Unclear and not necessary.
Response: The wording has been changed here.
Reviewer Comment: Line 100: "elements": Unclear. Do you mean grid boxes/columns?
Response: The wording here has been made more clear and with appropriate references given.
Reviewer Comment: Lines 283-285 + Figure 6b: How do you explain that the RMSE is as high in the HR simulations as in LR? Does this suggest that HR simulations are not realistic in reproducing spatial pattern of low clouds?
Response: Spatial patterns of low clouds are realistic in the HR simulations, as demonstrated by the geographical bias patterns in figure 4. Though, the bias is reduced locally in the stratocumulus regions, those regions are geographically quite small and thus does not have a dramatic effect on the global skill scores. In addition, it appears that the HR simulations have slightly more bias and error in the storm tracks, which is likely compensating the improved error scores in the stratocumulus regions.
Reviewer Comment: The variability of the COSP low-cloud amount may differ from the model cloud variability by changes in the high-cloud amount. How much does this influence the biases in the seasonal variability (Figure 12)? Overall, do the authors find the same result (improvement by FIVE, and HR) if using the model low-cloud amount?
Response: Using the model low-cloud amount (specifically the variable “CLDLOW”) produces nearly scientifically indistinguishable results when compared to using the LIDAR simulated low-cloud (“CLDLOW_CAL”). See attached figure (which uses CLDLOW) and compare that to figure 12.
Reviewer Comment: Line 370-371: What is the relative coverage of the SEP-RRM region? This would be a relevant comparison to the 0.05% the authors put forward.
Response: The SEP-RRM covers approximately 4.3% percent of the globe. This has been added to the text.
-
AC3: 'Reply on RC2', Peter Bogenschutz, 21 Nov 2022
Peer review completion
Interactive discussion
Status: closed
-
CEC1: 'Comment on gmd-2022-175', Astrid Kerkweg, 18 Aug 2022
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
So E3SM-FIVE including a version number / identifier should be added to the title of the article. Please add this change when submitting the revised version of the manuscript.
Additionally, the GMD editorial states about Model experiment description papers: "The primary purpose of these papers is to enable modelling communities to perform the same experiments. Therefore, everything required to run the experiment must be provided, apart from the model itself." (GMD Editorial main text, see also appendix B4)
I do not see that your article is about a model experiment which is performed by a larger community with different models. Therefore, your paper fits better the "Technical and development paper" type and I will ask the editorial office to apply this type to your article.
Yours, Astrid Kerkweg
- AC1: 'Reply on CEC1', Peter Bogenschutz, 21 Nov 2022
-
RC1: 'Comment on gmd-2022-175', Anonymous Referee #1, 20 Sep 2022
Bogenschutz et al. have presented a novel GCM framework that combines regional mesh refinement with vertically enhanced physics to improve simulated marine stratocumulus. The study addresses advancement in GCM and cloud modeling, which is well within the scope of GMD. Although previous studies have explored and documented the performance of regional mesh refinement and vertically enhanced physics separately in GCMs, the combination of the two is new. Therefore, this study presents a sufficiently substantial advance in modeling science. The paper is clearly written, well structured, and easy to follow. The conclusion, mainly that their novel framework can reproduce high resolution benchmark simulation with substantially lower computational cost, is well supported by the results.
I only have a few comments below:
L195-200: How is “low level cloud” defined?
L230-235: Presumably, Figure 5b shows the global impact of reduced SEP Sc bias. For example, it shows an increased low cloud amount along the ITCZ. Although it is not within the scope of this paper to discuss the global impact of reduced Sc bias, it would be helpful to provide information on whether the differences we see on Figure 5 are significant. This can help guide future work.
L290: In general, I would like to see more discussion on the mechanisms behind the improvement in SEP-RRM-FIVE. What processes lead to improved Sc with FIVE and with RRM respectively? Here the authors touched on turbulence and cloud top feedback. More detailed discussion would be appreciated.
L315-320: The presence of positive and negative bias along the coast in DJF, MMA, and SON in FIVE simulations suggests that the location of the Sc deck is shifted north of the observed Sc. Is this the case? If so, does it suggest that the bias is related to large-scale circulation instead of BL processes?
L330: “further refinement of the vertical grid in VEP could lead to additional improvements”, are there studies to support this claim?
-
AC2: 'Reply on RC1', Peter Bogenschutz, 21 Nov 2022
We thank Reviewer 1 for their time, comments, and helping to make this a better manuscript. Please see our reply to each comment below. For exact wording changes and additions made to the manuscript, please refer to the marked up manuscript.
Reviewer Comment: L195-200: How is “low level cloud” defined?
Response: Text has been added in the second paragraph of section 4.1 to address this and with reference given for the LIDAR retrieval.
Reviewer Comment: L230-235: Presumably, Figure 5b shows the global impact of reduced SEP Sc bias. For example, it shows an increased low cloud amount along the ITCZ. Although it is not within the scope of this paper to discuss the global impact of reduced Sc bias, it would be helpful to provide information on whether the differences we see on Figure 5 are significant. This can help guide future work.
Response: This is an excellent suggestion! We have added stippled areas to this plot to show where differences are statistically significant. In addition, text was modified/added in section 4.1 to discuss these results.
Reviewer Comment: L290: In general, I would like to see more discussion on the mechanisms behind the improvement in SEP-RRM-FIVE. What processes lead to improved Sc with FIVE and with RRM respectively? Here the authors touched on turbulence and cloud top feedback. More detailed discussion would be appreciated.
Response: Thank you for this suggestion. Yes, we agree more description and context was needed. At the end of section 4.1 we added a couple paragraphs to address this.
Reviewer Comment: L315-320: The presence of positive and negative bias along the coast in DJF, MMA, and SON in FIVE simulations suggests that the location of the Sc deck is shifted north of the observed Sc. Is this the case? If so, does it suggest that the bias is related to large-scale circulation instead of BL processes?
Response: This is a very interesting point and thus far our analysis has not shown strong evidence that the errors in the large-scale circulation are the leading cause of this placement bias. We hypothesize that parameterization deficiencies are the first order cause of the remaining bias, as already noted in the text.
Reviewer Comment: L330: “further refinement of the vertical grid in VEP could lead to additional improvements”, are there studies to support this claim?
Response: It was found in the original E3SM-FIVE prototype paper (Lee et al. 2021) that running with increased vertical resolution (16x relative to E3SM in the boundary layer) beyond that used in this paper (8x) has modest improvements to the Sc biases. Thus, It is possible that 16x vertical resolution in FIVE coupled with high horizontal resolution could further reduce the biases presented in this paper. The appropriate reference has been added near original line L330 (at the end of section 4.2) to support our speculation.
-
AC2: 'Reply on RC1', Peter Bogenschutz, 21 Nov 2022
-
RC2: 'Comment on gmd-2022-175', Anonymous Referee #2, 01 Nov 2022
Combining Regional Mesh RefinementWith Vertically Enhanced Physics to Target Marine Stratocumulus Biases
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
This study investigates the ability of improving the simulation of marine stratocumulus by modifying the vertical and horizontal resolutions. Since low clouds are more realistic in global high-resolution simulations, the authors test whether improving only the vertical resolution and /or locally refining the horizontal grid can reproduce this improvement. If so, this would lead to have better simulations with a relatively lower computational cost increase.
For that purpose, the authors analyze 6 global simulations: low, regionally-high, and high horizontal resolution, with and without high vertical resolutions (only for selected processes). They find that, firstly, having a finer vertical resolution for the parameterized processes, and secondly, refining the horizontal grid in the region of interest, significantly improves the simulation of marine stratocumulus (cloud amount and radiative effects). The authors conclude by advocating the usefulness of their framework for process-oriented analysis and sensitivity tests.
I find the article interesting and well written. The lack of improvement in representing stratocumulus and other boundary-layer clouds remains challenging. Therefore, the focus of the paper is of particular interest. Given the rise of global high-resolution modeling, it is important to provide insight into the effectiveness of improving low clouds with refined resolutions. However, I don't really understand how this happens. Using FIVE, some parameterized processes should be better represented, but it is not explained which of them mostly explains this difference, and how the changes act on the cloud coverage. Is it related to the way some processes are represented at the sub-grid scale and are sensitive to resolution (e.g. scale awareness)? Is it cloud-top entrainment, convective transport, turbulence closure, cloud radiation? This would help clarify why resolutions are so important, and how other climate modeling groups might use this framework.
So I thus suggest that the article be accepted after the minor comments I highlight. I would like to see the authors describe in more detail the reasons why vertical resolution is so important, and which processes are most sensitive to this refinement.
Specific comments:
- Line 59: "panacea": Unclear and not necessary.
- Line 100: "elements": Unclear. Do you mean grid boxes/columns?
- Lines 283-285 + Figure 6b: How do you explain that the RMSE is as high in the HR simulations as in LR? Does this suggest that HR simulations are not realistic in reproducing spatial pattern of low clouds?
- The variability of the COSP low-cloud amount may differ from the model cloud variability by changes in the high-cloud amount. How much does this influence the biases in the seasonal variability (Figure 12)? Overall, do the authors find the same result (improvement by FIVE, and HR) if using the model low-cloud amount?
- Line 370-371: What is the relative coverage of the SEP-RRM region? This would be a relevant comparison to the 0.05% the authors put forward.
-
AC3: 'Reply on RC2', Peter Bogenschutz, 21 Nov 2022
We thank Reviewer 2 for their time, comments, and helping to make this a better manuscript. Please see our reply to each comment below. For exact wording changes and additions made to the manuscript, please refer to the marked up manuscript.
Reviewer Comment: I find the article interesting and well written. The lack of improvement in representing stratocumulus and other boundary-layer clouds remains challenging. Therefore, the focus of the paper is of particular interest. Given the rise of global high-resolution modeling, it is important to provide insight into the effectiveness of improving low clouds with refined resolutions. However, I don't really understand how this happens. Using FIVE, some parameterized processes should be better represented, but it is not explained which of them mostly explains this difference, and how the changes act on the cloud coverage. Is it related to the way some processes are represented at the sub-grid scale and are sensitive to resolution (e.g. scale awareness)? Is it cloud-top entrainment, convective transport, turbulence closure, cloud radiation? This would help clarify why resolutions are so important, and how other climate modeling groups might use this framework.
So I thus suggest that the article be accepted after the minor comments I highlight. I would like to see the authors describe in more detail the reasons why vertical resolution is so important, and which processes are most sensitive to this refinement.
Response: Thank you for this excellent suggestion. Yes, we agree more description and context was needed. At the end of section 4.1 we added a couple paragraphs to address this.
Specific comments:
Reviewer Comment: Line 59: "panacea": Unclear and not necessary.
Response: The wording has been changed here.
Reviewer Comment: Line 100: "elements": Unclear. Do you mean grid boxes/columns?
Response: The wording here has been made more clear and with appropriate references given.
Reviewer Comment: Lines 283-285 + Figure 6b: How do you explain that the RMSE is as high in the HR simulations as in LR? Does this suggest that HR simulations are not realistic in reproducing spatial pattern of low clouds?
Response: Spatial patterns of low clouds are realistic in the HR simulations, as demonstrated by the geographical bias patterns in figure 4. Though, the bias is reduced locally in the stratocumulus regions, those regions are geographically quite small and thus does not have a dramatic effect on the global skill scores. In addition, it appears that the HR simulations have slightly more bias and error in the storm tracks, which is likely compensating the improved error scores in the stratocumulus regions.
Reviewer Comment: The variability of the COSP low-cloud amount may differ from the model cloud variability by changes in the high-cloud amount. How much does this influence the biases in the seasonal variability (Figure 12)? Overall, do the authors find the same result (improvement by FIVE, and HR) if using the model low-cloud amount?
Response: Using the model low-cloud amount (specifically the variable “CLDLOW”) produces nearly scientifically indistinguishable results when compared to using the LIDAR simulated low-cloud (“CLDLOW_CAL”). See attached figure (which uses CLDLOW) and compare that to figure 12.
Reviewer Comment: Line 370-371: What is the relative coverage of the SEP-RRM region? This would be a relevant comparison to the 0.05% the authors put forward.
Response: The SEP-RRM covers approximately 4.3% percent of the globe. This has been added to the text.
-
AC3: 'Reply on RC2', Peter Bogenschutz, 21 Nov 2022
Peer review completion
Journal article(s) based on this preprint
Peter A. Bogenschutz et al.
Peter A. Bogenschutz et al.
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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.
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