the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new process-based and scale-aware desert dust emission scheme for global climate models – Part II: evaluation in the Community Earth System Model (CESM2)
Abstract. Desert dust is an important atmospheric aerosol that affects the Earth's climate, biogeochemistry, and air quality. However, current Earth system models (ESMs) struggle to accurately capture the impact of dust on the Earth’s climate and ecosystems, in part because these models lack several essential aeolian processes that couple dust with climate and land surface processes. In this study, we address this issue by implementing several new parameterizations of aeolian processes detailed in our companion paper into the Community Earth System Model version 2 (CESM2). These processes include (1) incorporating a realistic soil particle size distribution to calculate the dust emission threshold friction velocity, (2) accounting for the drag partition effect of rocks and vegetation in reducing wind stress on erodible soils, (3) accounting for the intermittency of dust emissions due to unresolved turbulent wind fluctuations, and (4) correcting the spatial variability of simulated dust emissions from native to higher spatial resolutions on spatiotemporal dust variability. Our results show that the modified dust emission scheme significantly reduces the model bias against observations compared to the default scheme and improves the correlation against observations of multiple key dust variables such as dust aerosol optical depth (DAOD), surface particulate matter (PM) concentration, and deposition flux. Our scheme’s dust also correlates strongly with various meteorological and land surface variables, implying higher sensitivity of dust to future climate change than other schemes’ dust. These findings highlight the importance of including additional aeolian processes for improving the performance of ESM aerosol simulations and potentially enhancing model assessments of how dust impacts climate and ecosystem changes.
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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
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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
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Supplement
(7116 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-823', Anonymous Referee #1, 05 Jul 2023
This paper summarizes an important work on improving the dust emission representation in CESM2. Overall the paper is well written and presents sufficient analysis of the dust model performance. I have some comments and questions, described as below.
Given the complexity of the model, consider adding a table to list all the mathematical symbols and abbreviations defined in the paper, and/or a flowchart of the model components.
Section 3.3:
Clarify whether Feff in Eq. 7 represents the fraction of wind drag available for dust lifting or consumed by non-erodible materials, to avoid confusion of the readers.Section 3.4:
What is the physical rationale of representing the intermittent dust emission simply as a scaling factor on the saltation-driven dust emission? Turbulent/convective and saltation-driven dust emissions are two separate physical processes, and have their own separate forms of model parameterizations.Also, I understand the authors' goal of incorporating as many physical processes as possible, which however may not always improve the model. I am curious whether the importance of dust emission intermittency is evaluated, e.g., via sensitivity analysis? Fig. S2 shows the intermittency factor is much like a global erodible fraction map with high values over subtropical regions, and low values elsewhere.
Section 3.5:
The purpose is upscaling correction map (Kc) is explained, but confusing. If the authors intend to capture the finer-scale variability in wind and dust emission, why not just increase the model resolution? I assume computational resources is not a limiting factor since it's not mentioned in the paper.A standalone experiment is performed to calculate Kc. What's the time period of the standalone experiment? Does Kc vary significantly in time, e.g., between seasons and from year to year? If yes, explain why applying a constant Kc is acceptable for the multi-year simulation.
Section 5.2
Since MIDAS relies on MERRA2 for deriving DAOD, it's subject to MERRA2 aerosol model biases in addition to MODIS sensor/algorithm errors. What's the implication for the comparison with CESM2 model performance?Section 5.3 Line 785, any proof that the DAOD over Taklamakan has mixed signals from Karakum/Kyzylkum? Those are two desert regions separated by high mountains - there is a very small chance the dust from either one is transported to the other.
How does the dust emission amount affect the temporal (daily) correlation of DAOD? Could meteorology be important?
I find the authors' explanation of the model underperformance over China speculative at best.Citation: https://doi.org/10.5194/egusphere-2023-823-RC1 -
RC2: 'Comment on egusphere-2023-823', Anonymous Referee #2, 31 Aug 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-823/egusphere-2023-823-RC2-supplement.pdf
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AC1: 'Comment on egusphere-2023-823', Danny Leung, 02 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-823/egusphere-2023-823-AC1-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-823', Anonymous Referee #1, 05 Jul 2023
This paper summarizes an important work on improving the dust emission representation in CESM2. Overall the paper is well written and presents sufficient analysis of the dust model performance. I have some comments and questions, described as below.
Given the complexity of the model, consider adding a table to list all the mathematical symbols and abbreviations defined in the paper, and/or a flowchart of the model components.
Section 3.3:
Clarify whether Feff in Eq. 7 represents the fraction of wind drag available for dust lifting or consumed by non-erodible materials, to avoid confusion of the readers.Section 3.4:
What is the physical rationale of representing the intermittent dust emission simply as a scaling factor on the saltation-driven dust emission? Turbulent/convective and saltation-driven dust emissions are two separate physical processes, and have their own separate forms of model parameterizations.Also, I understand the authors' goal of incorporating as many physical processes as possible, which however may not always improve the model. I am curious whether the importance of dust emission intermittency is evaluated, e.g., via sensitivity analysis? Fig. S2 shows the intermittency factor is much like a global erodible fraction map with high values over subtropical regions, and low values elsewhere.
Section 3.5:
The purpose is upscaling correction map (Kc) is explained, but confusing. If the authors intend to capture the finer-scale variability in wind and dust emission, why not just increase the model resolution? I assume computational resources is not a limiting factor since it's not mentioned in the paper.A standalone experiment is performed to calculate Kc. What's the time period of the standalone experiment? Does Kc vary significantly in time, e.g., between seasons and from year to year? If yes, explain why applying a constant Kc is acceptable for the multi-year simulation.
Section 5.2
Since MIDAS relies on MERRA2 for deriving DAOD, it's subject to MERRA2 aerosol model biases in addition to MODIS sensor/algorithm errors. What's the implication for the comparison with CESM2 model performance?Section 5.3 Line 785, any proof that the DAOD over Taklamakan has mixed signals from Karakum/Kyzylkum? Those are two desert regions separated by high mountains - there is a very small chance the dust from either one is transported to the other.
How does the dust emission amount affect the temporal (daily) correlation of DAOD? Could meteorology be important?
I find the authors' explanation of the model underperformance over China speculative at best.Citation: https://doi.org/10.5194/egusphere-2023-823-RC1 -
RC2: 'Comment on egusphere-2023-823', Anonymous Referee #2, 31 Aug 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-823/egusphere-2023-823-RC2-supplement.pdf
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AC1: 'Comment on egusphere-2023-823', Danny Leung, 02 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-823/egusphere-2023-823-AC1-supplement.pdf
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Jasper F. Kok
Longlei Li
Natalie M. Mahowald
David M. Lawrence
Simone Tilmes
Erik Kluzek
Martina Klose
Carlos Pérez García-Pando
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(9648 KB) - Metadata XML
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Supplement
(7116 KB) - BibTeX
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- Final revised paper