the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A single-point modeling approach for the intercomparison and evaluation of ozone dry deposition across chemical transport models (Activity 2 of AQMEII4)
Olivia Elaine Clifton
Donna Schwede
Christian Hogrefe
Jesse O. Bash
Sam Bland
Philip Cheung
Mhairi Coyle
Lisa Emberson
Johannes Flemming
Erick Fredj
Stefano Galmarini
Laurens Ganzeveld
Orestis Gazetas
Ignacio Goded
Christopher D. Holmes
László Horváth
Vincent Huijnen
Qian Li
Paul A. Makar
Ivan Mammarella
Giovanni Manca
J. William Munger
Juan L. Pérez-Camanyo
Jonathan Pleim
Limei Ran
Roberto San Jose
Sam J. Silva
Ralf Staebler
Shihan Sun
Amos P. K. Tai
Timo Vesala
Tamás Weidinger
Zhiyong Wu
Leiming Zhang
Abstract. A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models yet an understanding of the model spread is incomplete. Here we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine dry deposition schemes from regional and global chemical transport models as well as standalone models used for impacts assessments or process understanding. We configure eighteen schemes as single-point models at eight northern hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least three years and up to twelve years of ozone fluxes. The spread across models that de-emphasizes outliers in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared to summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree in relative contributions from the pathways, even when they predict similar deposition velocities, or agree in the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in chemical transport models used for research, planning, and regulatory purposes.
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Olivia Elaine Clifton et al.
Status: open (extended)
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RC1: 'Comment on egusphere-2023-465', Anonymous Referee #1, 05 May 2023
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This manuscript provides a comprehensive intercomparison between established ozone dry deposition parameterizations. The result is somewhat expected but still highly relevant and valuable for the community, established with robust result. I have only a few minor questions and suggestions:
- The model description is nice and thorough. However, putting them in the main text obstruct the flow of the manuscript. I suggest the authors move the detailed model description to appendix/supplemental material. The authors could also consider using tables to make the model description more organized and readable.
- L 79 – 80: I suggest “land carbon sink” instead of “carbon storage, and more example/elaboration about how ozone affect ecosystem service
- Table 1: What precisely is B? “Parameter related to soil moisture” sounds very vague.
- L 228 – 230: More discussion about how the uncertainty in ra (choice of MOST universal function, h and z0) may (or may not) affect the study can be helpful.
- L 284 – 285: Clarify what is “effective LAI”. What is its physical/biological meaning? How is it calculated?
- L 841: What “other compounds” and why are they “challenging” to be measured in high frequency? Some examples, discussions and citations would be helpful.
- L 1728: Could the authors provide how may we address the over-reliance on LAI to determine seasonality? E.g. Would other ecophysiological parameters (e.g. seasonally-varying leaf nitrogen content/leaf-level photosynthetic capacity) help? What factors other than phenology might contribute to the seasonality of vd, but not yet considered in the parameterizations? Is the seasonality of non-stomatal ozone uptake under-represented?
Citation: https://doi.org/10.5194/egusphere-2023-465-RC1
Olivia Elaine Clifton et al.
Olivia Elaine Clifton et al.
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