the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Apr 2023
Emulating lateral gravity wave propagation in a global chemistry-climate model (EMAC v2.55.2) through horizontal flux redistribution
Sebastian Rhode
Hella Garny
Peter Preusse
Petr Pisoft
Aleš Kuchar
Patrick Jöckel
Astrid Kerkweg
Bastian Kern
Abstract. The columnar approach of gravity wave (GW) parameterisations in weather and climate models has been identified as a potential reason for dynamical biases in middle atmospheric dynamics. For example, GW momentum flux (GWMF) discrepancies between models and observations at 60° S arising through the lack of horizontal orographic GW propagation is suspected to cause deficiencies in representing the Antarctic polar vortex. However, due to the decomposition of the model domains onto different computing tasks for parallelisation, communication between horizontal grid boxes is computationally extremely expensive, making horizontal propagation of GWs unfeasible for global chemistry-climate simulations.
To overcome this issue, we here present a simplified solution approximating horizontal GW propagation through redistribution of the GWMF at one single altitude by means of tailor-made redistribution maps. To generate the global redistribution maps averaged for each grid box, we use a parameterisation describing orography as a set of mountain ridges with specified location, orientation and height combined with a ray-tracing model describing lateral propagation of so-generated mountain waves. In the global chemistry-climate model (CCM) EMAC (ECHAM MESSy Atmospheric Chemistry), these maps then allow us to redistribute the GW momentum flux horizontally at one level obtaining an affordable overhead of computing resources. The results of our simulations show GWMF and drag patterns which are horizontally more spread-out than with the purely columnar approach, GWs now also are present above the ocean and regions without mountains. In this paper, we provide a detailed description of how the redistribution maps are computed and how the GWMF redistribution is implemented in the CCM. Moreover, an analysis shows why 15 km is the ideal altitude for the redistribution. First results with the redistributed orographic GWMF provide clear evidence that the redistributed GW drag in the Southern Hemisphere has the potential to modify and improve Antarctic polar vortex dynamics, thereby paving the way for enhanced credibility of CCM simulations and projections of polar stratospheric ozone.
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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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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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- Final revised paper
Journal article(s) based on this preprint
Roland Eichinger et al.
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-270', Anonymous Referee #1, 28 May 2023
Orographic gravity waves (OGWs) propagate obliquely in reality while current parameterization schemes assume vertical propagation which is a long-stanging known problem. Using the approach of horizontal flux redistribution, this work studies the parameterization of lateral gravity wave propagation in a global chemistry-climate model. This is an important step toward accurate representation of OGWs in climate models. The paper is scientific sounding and worthy publication. But there are still some issuses to be clarified. So I recomment major revsion.
- Why are MWs assumed to be perpendicular to the source ridge? In reality, the winds can be oblique to the ridge.
- L136: The resolution of ERA5 is 0.25 degree, right?
- Do you mean there are many ridges within a grid cell? I’m confused about this because, in OGWD parameterization, only a dominant ridge is considered within one grid cell.
- Remove “it was used” which appears to be redundant.
- About Figure 3. Firstly, why the GWMF of NO_HOR is less than those redistributed ones in the lower altitudes (especially below 10 km)? Wouldn’t it be greater in the absence of lateral propagation of OGWs? Secondly, why are the GWMFs different for different Htar? Taking Htar = 40 km and 45 km for example, they should be the same below 40 km since no lateral propagation below this level for both cases, right?
- About the implementation in L264-273. When applying the lateral propagation, how far can the parameterized OGWs propagate in the horizontal direction? In other words, is there an upper limit of horizontal distance for the lateral propagation of OGWs? Moreover, can you talk about the potential influence of applying the redistribution only at one single altitude level? Clearly, the OGWs propagate more and more laterally with height. Applying at single level means omitting the lateral propagation below this level and underestimation above this level. Is it possible to apply the lateral propagation at full altitudes? In this case, Zoro is not a dynamic parameter (L309) and you don’t have to calculate Eq. (5), right?
- Why the map is 4D? Is it time-varying and spatially different?
- Ok, the authors stated that the map is temporally constant. How about using a time-varying map, at least monthly variation? (see the notably monthly variation in Fig.4a)
- Is it possible that the difference between the total GW drag may be due to the different wind circulations in these two experiments which determine the wave source and breaking?
Citation: https://doi.org/10.5194/egusphere-2023-270-RC1 - AC1: 'Reply on RC1', Roland Eichinger, 10 Aug 2023
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RC2: 'Comment on egusphere-2023-270', Anonymous Referee #2, 19 Jul 2023
Review of manuscript egusphere-2023-270 submmitted to Geophysical Model Development: “Emulating lateral gravity wave propagation in a global chemistry-climate model (EMAC v2.55.2) through horizontal flux redistribution”, by Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchař, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern.
This study proposes a relatively cheap computational shortcut to emulate the effects of three-dimensional propagation of gravity waves (GWs) in GW drag parameterizations for climate models. This is done by a horizontal redistribution of GW momentum flux at a given level in the lower stratosphere, which is achieved with the construction of a redistribution map derived from a GW ray-tracing model. The method is applied to the model EMAC and found that the orographic GW drag gap at 60ºS that all models produce due to the columnar approach of parameterizations is completely reduced, which seems to improve the final warming date of the austral polar vortex in the model.
The paper is clearly written and the method and results are relevant, the vertical and horizontal distribution of parameterized GW momentum flux being an identified source of systematic biases in the the simulation of the middle atmosphere in climate models. I only have a few minor comments listed below.
Comments:
- Section 2.1: What is the reason of using idealized, Gaussian-shaped mountain ridges for the MW parameterization?
- Eq 3. Just a clarification, the terminology may have confused me: the momentum flux \tau_{m1} that is being redistributed is taken at the model level 65, right below 15 km. And this model level is labeled “src” in eq (3)? So “src” is not the GWMF at source level in the parameterization, but at the chosen level for redistribution?
- Figs. 8 and 9, Lines 405 and 450: Regarding the increased drag at upper levels with redistributed flux, part of the reason of this behavior might indeed be due to more favorable vertical propagation conditions around the polar night jet. If a fraction of the momentum flux generated at the Andes and the Antarctic Peninsula is redistributed around 60S, where the zonal mean wind maximum is located, the saturated flux given by eq. (4) would be larger, hence allowing the waves to propagate upwards without dissipating. Does this make sense? Plougonven et al. (2017) reported a tendency in observations and high resolution simulations for large momentum fluxes to be located at the jet maximum, which was explained in terms of horizontal propagation.
- Fig. 11. I would suggest to add some panels to this figure showing the comparison with ERA5, this would be valuable to assess whether the implemented redistribution works in the right direction, with all the caveats regarding the lack of refined tuning.
- Although the interaction between the modified GW drag, planetary wave driving and the mean circulation well deserves a separate study, it would be very interesting to briefly analyze changes in planetary wave driving in these 4 EMAC runs. I would suggest to add the corresponding latitudinal distribution of WP flux divergence to the panels in Fig. 10. According to Garcia et al (2017), there is a strong compensation between GW drag and resolved forcing around 60S due to the columnar approach followed by orographic GW parameterizations. Besides, these plot may help explain to a first order the changes in the zonal mean zonal winds and temperatures given in Fig. 11.
References:
Plougonven, R., V. Jewtoukoff, A. de la Cámara, F. Lott, and A. Hertzog (2017): On the Relation between Gravity Waves and Wind Speed in the Lower Stratosphere over the Southern Ocean, J. Atmos. Sci., 74, 1075-1093, doi: 10.1175/JAS-D-16-0096.1.
Garcia, R. R., A. K. Smith, D. E. Kinnison, A. de la Cámara, and D. J. Murphy (2017): Modification of the Gravity Wave Parameterization in the Whole Atmosphere Community Climate Model: Motivation and Results, J. Atmos. Sci., 74, 275-291, doi: 10.1175/JAS-D-16-0104.1.
Citation: https://doi.org/10.5194/egusphere-2023-270-RC2 - AC2: 'Reply on RC2', Roland Eichinger, 10 Aug 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-270', Anonymous Referee #1, 28 May 2023
Orographic gravity waves (OGWs) propagate obliquely in reality while current parameterization schemes assume vertical propagation which is a long-stanging known problem. Using the approach of horizontal flux redistribution, this work studies the parameterization of lateral gravity wave propagation in a global chemistry-climate model. This is an important step toward accurate representation of OGWs in climate models. The paper is scientific sounding and worthy publication. But there are still some issuses to be clarified. So I recomment major revsion.
- Why are MWs assumed to be perpendicular to the source ridge? In reality, the winds can be oblique to the ridge.
- L136: The resolution of ERA5 is 0.25 degree, right?
- Do you mean there are many ridges within a grid cell? I’m confused about this because, in OGWD parameterization, only a dominant ridge is considered within one grid cell.
- Remove “it was used” which appears to be redundant.
- About Figure 3. Firstly, why the GWMF of NO_HOR is less than those redistributed ones in the lower altitudes (especially below 10 km)? Wouldn’t it be greater in the absence of lateral propagation of OGWs? Secondly, why are the GWMFs different for different Htar? Taking Htar = 40 km and 45 km for example, they should be the same below 40 km since no lateral propagation below this level for both cases, right?
- About the implementation in L264-273. When applying the lateral propagation, how far can the parameterized OGWs propagate in the horizontal direction? In other words, is there an upper limit of horizontal distance for the lateral propagation of OGWs? Moreover, can you talk about the potential influence of applying the redistribution only at one single altitude level? Clearly, the OGWs propagate more and more laterally with height. Applying at single level means omitting the lateral propagation below this level and underestimation above this level. Is it possible to apply the lateral propagation at full altitudes? In this case, Zoro is not a dynamic parameter (L309) and you don’t have to calculate Eq. (5), right?
- Why the map is 4D? Is it time-varying and spatially different?
- Ok, the authors stated that the map is temporally constant. How about using a time-varying map, at least monthly variation? (see the notably monthly variation in Fig.4a)
- Is it possible that the difference between the total GW drag may be due to the different wind circulations in these two experiments which determine the wave source and breaking?
Citation: https://doi.org/10.5194/egusphere-2023-270-RC1 - AC1: 'Reply on RC1', Roland Eichinger, 10 Aug 2023
-
RC2: 'Comment on egusphere-2023-270', Anonymous Referee #2, 19 Jul 2023
Review of manuscript egusphere-2023-270 submmitted to Geophysical Model Development: “Emulating lateral gravity wave propagation in a global chemistry-climate model (EMAC v2.55.2) through horizontal flux redistribution”, by Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchař, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern.
This study proposes a relatively cheap computational shortcut to emulate the effects of three-dimensional propagation of gravity waves (GWs) in GW drag parameterizations for climate models. This is done by a horizontal redistribution of GW momentum flux at a given level in the lower stratosphere, which is achieved with the construction of a redistribution map derived from a GW ray-tracing model. The method is applied to the model EMAC and found that the orographic GW drag gap at 60ºS that all models produce due to the columnar approach of parameterizations is completely reduced, which seems to improve the final warming date of the austral polar vortex in the model.
The paper is clearly written and the method and results are relevant, the vertical and horizontal distribution of parameterized GW momentum flux being an identified source of systematic biases in the the simulation of the middle atmosphere in climate models. I only have a few minor comments listed below.
Comments:
- Section 2.1: What is the reason of using idealized, Gaussian-shaped mountain ridges for the MW parameterization?
- Eq 3. Just a clarification, the terminology may have confused me: the momentum flux \tau_{m1} that is being redistributed is taken at the model level 65, right below 15 km. And this model level is labeled “src” in eq (3)? So “src” is not the GWMF at source level in the parameterization, but at the chosen level for redistribution?
- Figs. 8 and 9, Lines 405 and 450: Regarding the increased drag at upper levels with redistributed flux, part of the reason of this behavior might indeed be due to more favorable vertical propagation conditions around the polar night jet. If a fraction of the momentum flux generated at the Andes and the Antarctic Peninsula is redistributed around 60S, where the zonal mean wind maximum is located, the saturated flux given by eq. (4) would be larger, hence allowing the waves to propagate upwards without dissipating. Does this make sense? Plougonven et al. (2017) reported a tendency in observations and high resolution simulations for large momentum fluxes to be located at the jet maximum, which was explained in terms of horizontal propagation.
- Fig. 11. I would suggest to add some panels to this figure showing the comparison with ERA5, this would be valuable to assess whether the implemented redistribution works in the right direction, with all the caveats regarding the lack of refined tuning.
- Although the interaction between the modified GW drag, planetary wave driving and the mean circulation well deserves a separate study, it would be very interesting to briefly analyze changes in planetary wave driving in these 4 EMAC runs. I would suggest to add the corresponding latitudinal distribution of WP flux divergence to the panels in Fig. 10. According to Garcia et al (2017), there is a strong compensation between GW drag and resolved forcing around 60S due to the columnar approach followed by orographic GW parameterizations. Besides, these plot may help explain to a first order the changes in the zonal mean zonal winds and temperatures given in Fig. 11.
References:
Plougonven, R., V. Jewtoukoff, A. de la Cámara, F. Lott, and A. Hertzog (2017): On the Relation between Gravity Waves and Wind Speed in the Lower Stratosphere over the Southern Ocean, J. Atmos. Sci., 74, 1075-1093, doi: 10.1175/JAS-D-16-0096.1.
Garcia, R. R., A. K. Smith, D. E. Kinnison, A. de la Cámara, and D. J. Murphy (2017): Modification of the Gravity Wave Parameterization in the Whole Atmosphere Community Climate Model: Motivation and Results, J. Atmos. Sci., 74, 275-291, doi: 10.1175/JAS-D-16-0104.1.
Citation: https://doi.org/10.5194/egusphere-2023-270-RC2 - AC2: 'Reply on RC2', Roland Eichinger, 10 Aug 2023
Peer review completion
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Roland Eichinger et al.
Roland Eichinger 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.
- Preprint
(5801 KB) - Metadata XML
-
Supplement
(8704 KB) - BibTeX
- EndNote
- Final revised paper