the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Tropospheric transport and unresolved convection: numerical experiments with CLaMS-2.0/MESSy
- 1Forschungszentrum Jülich, IEK-7, Germany
- 2Carbon Neutrality Research Center, Institute of Atmospheric Physics, Beijing, China
- 3Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany
- 4National Research Council - Institute for Atmospheric Sciences and Climate (ISAC-CNR), 40129 Bologna, Italy
- 5Institute for Atmospheric and Environmental Research, University of Wuppertal, Wuppertal, Germany
- 6The Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology, Karlsruhe, Germany
- 7Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
- anow at: Laboratoire de Physique et Chimie de l’Environnement et de l’Espace (LPC2E), Universitè d’Orlèans, France
- 1Forschungszentrum Jülich, IEK-7, Germany
- 2Carbon Neutrality Research Center, Institute of Atmospheric Physics, Beijing, China
- 3Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany
- 4National Research Council - Institute for Atmospheric Sciences and Climate (ISAC-CNR), 40129 Bologna, Italy
- 5Institute for Atmospheric and Environmental Research, University of Wuppertal, Wuppertal, Germany
- 6The Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology, Karlsruhe, Germany
- 7Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
- anow at: Laboratoire de Physique et Chimie de l’Environnement et de l’Espace (LPC2E), Universitè d’Orlèans, France
Abstract. Pure Lagrangian, i.e.~trajectory-based transport models, take into account only the resolved advective part of transport. That means neither mixing processes between the air parcels (APs) nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS-1.0) extends this approach by including mixing between the Lagrangian APs parameterizing the small-scale isentropic mixing. To improve model representation of the upper troposphere and lower stratosphere (UTLS), this approach was extended by taking into account parameterization of tropospheric mixing and unresolved convection in the recently published CLaMS-2.0 version. All three transport modes, i.e. isentropic and tropospheric mixing as well as the unresolved convection can be adjusted and optimized within the model. Here, we investigate the sensitivity of the model representation of tracers in the UTLS with respect to these three modes.
For this reason, the CLaMS-2.0 version implemented within the Modular Earth Submodel System (MESSy), CLaMS-2.0/MESSy, is applied with meteorology based on the ERA-Interim (EI) and ERA5 (E5) reanalyses with the same horizontal resolution (1.0 x 1.0 degree) but with 60 and 137 model levels for EI and E5, respectively. Comparisons with in situ observations are used to rate the degree of agreement between different model configurations and observations. Starting from pure advective runs as a reference and in agreement with CLaMS-1.0, we show that among the three processes considered, isentropic mixing dominates transport in the UTLS. Both the observed CO, O3, N2O and CO2 profiles as well as CO-O3 correlations are clearly better reproduced in the model with isentropic mixing. The second most important transport process considered is unresolved convection. This additional pathway of transport from the Planetary Boundary Layer (PBL) to the main convective outflow dominates the composition of air in the lower stratosphere relative to the contribution of the resolved transport. This transport happens mainly in the tropics and sub-tropics, and significantly rejuvenates the age of air in this region. By taking into account tropospheric mixing, weakest changes in tracer distributions without any clear improvements were found.
Paul Konopka et al.
Status: open (until 13 Jul 2022)
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RC1: 'Comment on gmd-2022-97', Anonymous Referee #1, 16 Jun 2022
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This paper describes a new version 2.0 of the CLAMS-MESSY chemistry-transport model. The model is Lagrangian and follows isolated air parcels (APs) around the atmosphere, being required every so often to remap the parcels because there will be regions with a glut, and regions deserted by the APs. The real art here is remapping onto a std grid or figuring out how to remove and add parcels. The new model presented here includes inter-Parcel exchange via "parameterization of tropospheric mixing and unresolved convection." What is worrisome here is that there is no clear atmospheric physics to determine the rate of mixing, but rather it is just tuned and is defined to represent a type of mixing. It appears that CLaMS-2.0 has already been published and this paper is an application of it. If so, is this a GMD paper or an ACP one? I am not too worried about which, but the editor may wish to weigh in.
Overall, this is a reasonably nice paper, written clearly and deserves to be published after some thought and revision. I include comments by line number below.
L15 "The second most important transport process considered is unresolved convection." I remain very confused by this term: if the convection is not resolved in the EC fields (which it is resolved explicitly in the fields I use from the IFS system) then how can CLAMS use it? Just make up a covnective rate?
PLEASE use continuous number, discerning page number as well as line numbers is not nice. I cannot see page number when reading your paper on a screen. Thus I may not get the page numbers correct in my comments.
P2L5 "reduced numerical diffusion compared 5 to the Eulerian-based transport models" I am tired of Lagrangrian models mantra that Eulerian are more diffusive. Some tracer transport Eulerian schemes have negligible diffusion – please see the Lauritzen papers (Geosci. Model Dev., 7, 105–145, doi:10.5194/gmd-7-105-2014 and Geosci. Model Dev., 5, 887–901, doi:10.5194/gmd-5-887-2012. Both methods have their advantages, but you need to retract the old arguments.
L13: " perpetuum runs are performed (14-times 2017) as" This is a very bad approach if you are serious looking at the strat-trop region, because at Jan 1 there is a huge discontinuity in the tropopause and jet stream every annual cycle. This creates havoc with lots of instant strat-2-trop placement of ozone in the troposphere (and vice versa).
L18: " three parameterized components of transport: isentropic mixing (I), unresolved convection (C) and tropospheric mixing (T) schematically" If these are all parameterized and not based on atmospheric physics then I do nto see how you are running ERA fields. There is only a certain amount of such mixing that is consistent with the wind fields. I fear that your model is inconsistent with the ERA model result.
P4. The table shows a worrying feature. You have only the instant winds every 6 hours. You really need 3-hour fields if you are going to resolve any diurnal cycles, such as BL mixing. With 6h, you alias all these cycles at different points as you cross longitudes. It seems like your mixing parameters are arbitrarily selected and not related to the local meteorology. I cannot understand it.
P5: The tracer results are interesting, nice job on the mix of real and synthetic tracers. For example, based on the e90 work, the new mixing in CLAMS-2 is essential in maintaining a clean tropopause. Figure 3, is a very nice representation of the consequences of the mixing.
P18 Conclusions. These are reasonable and rational and accurately describe the model results shown here. The AoA spectrum at 350K is interesting and shows a burst of young air with the new parameterizations. What is unclear is whether this carries on to 380-400K. The Hoffman 2022 results sound very interesting, is it limited to the lower stratosphere with very stable layering? Unfortunately, the paper is still being written (and should probably not be used as a reference here).
Overall, what I am worried about is that the mixing is set by the modelers based on a type of mixing, but it does not respond to atmospheric physics (did I miss something here). Can the authors get the statistics (e.g., like Tiedtke convective fluxes or BL heights and mixing) from the ERA fields?
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RC2: 'Comment on gmd-2022-97', Anonymous Referee #2, 19 Jun 2022
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This manuscript is an interesting contribution to the technology of atmospheric transport model, extending the series of works made with CLaMS. The main conclusion is that parametrized convective fluxes are necessary to perform realistic transport from the boundary layer to the UTLS, especially in the tropical region where no conveyor belt is operating, and I ready to accept that. The paper is on the overall well written and I have only a few minor comments to forward to the authors.
1 - My only significant reservation is about the usage of the e90 tracer. Prather et al. (2011) say that the 90 ppbv value fits the tropopause for their given CTM and meteorology but there is no reason to use it as a general reference since there is by definition no observational constrain for such an artificial tracer. It is OK to use e90 in order to characterize the overall structure and time-scale of the tropospheric overturning circulation but I do not think that the comparison of the 90 ppbv surface with the WMO tropopause in Fig.3 can be used to score the versions of the model. In all panels of Fig.2, there are other surfaces with large gradients that fit as well the tropopause than the I1C1 surfaces in Fig.3.
2 - The paper is written in an incremental mode and could be somewhat difficult to follow for someone who is not already familiar with CLaMS and the terminology that is proper to this model. Perhaps this is the intended audience but I would find useful to have a few general definition of notions like tropospheric mixing, pure advective mode and so on. The new epsilon parameter is defined is the appendix but this is again very cryptic if you do not know anything about CLaMS.
3 - It takes some time to understand and follow the awkward naming convention of the runs. At first, the table 2 does not make sense. Perhaps a more detailed description would help. It is not necessary to name the experiments in a publication in the same way as the directories on the computer.
4 - The parametrized convection is based on a fairly crude scheme, of the type that has been rejected long ago in the numerical weather forecast to the benefit of more sophisticated schemes which are found necessary to better represent the convective timing and organisation, and the convective fluxes. I understand that the present scheme used in CLaMS is better than nothing but why not using the convective fluxes of the ERA5 which are archived and available along the meteorological data used in this study. This will not be perfect as there are still many biases in such scheme but is would be more in pace with the state of the art in convective parametrization with the sole cost of additional storage. Off course, this suggestion is aimed only at future work.
5 – I would have liked to see a more detailed discussion of the effect of convective parametrization on p. 7, for instance about the meridional gradients associated with the Hadley circulation.
6 – I am puzzled by the discrepancies of CO2 in the boundary layer where it is forced by Carbon Tracker. Is it that Carbon Tracker misses the biological carbon cycle and in which way is it local ?
7 – I do not understand why the black reference dots are different in the various panels of Fig. 6 and I do not understand either why the modelled cloud is closer to the reference in panel b that in panel a with apparently the same values of d. Perhaps this is an effect of the linear color scale that does not display the difference among small values.
8- There are two modes in Fig. A0 that should be distinguished, a UT tropical mode on the left which is strongly affected by the convection and a LS extra-tropical mode on the right which is only affected by mixing.
9- The authors should check the DOI numbers in the reference list. At least one (Konopka et al., 2019), the one I tried, points to another paper.
Paul Konopka et al.
Paul Konopka et al.
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