EGU General Assembly 2020
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the Creative Commons Attribution 4.0 License.

The influence of transport model resolution on the inverse modelling of synthetic greenhouse gas emissions in Switzerland

Ioannis Katharopoulos1,2, Dominique Rust2, Martin Vollmer2, Dominik Brunner2,1, Stefan Reimann2, Lukas Emmenegger2, and Stephan Henne2
Ioannis Katharopoulos et al.
  • 1Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology Zurich, Universitaetstrasse 16, CHN, 8092 Zurich, Switzerland
  • 2Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, Dübendorf, Switzerland

Climate change is one of the biggest challenges of the modern era. Halocarbons contribute already about 14% to current anthropogenic radiative forcing, and their future impact may become significantly larger due to their long atmospheric lifetimes and continued and increasing usage. In addition to their influence on climate change, chlorine and bromine-containing halocarbons are the main drivers of the destruction of the stratospheric ozone layer. Therefore, observing their atmospheric abundance and quantifying their sources is critical for predicting the related future impact on climate change and on the recovery of the stratospheric ozone layer.

Regional scale atmospheric inverse modelling can provide observation-based estimates of greenhouse gas emissions at a country scale and, hence, makes valuable information available to policy makers when reviewing emission mitigation strategies and confirming the countries' pledges for emission reduction. Considering that inverse modelling relies on accurate atmospheric transport modelling any advances to the latter are of key importance. The main objective of this work is to characterize and improve the Lagrangian particle dispersion model (LPDM) FLEXPART-COSMO at kilometer-scale resolution and to provide estimates of Swiss halocarbon emissions by integrating newly available halocarbon observations from the Swiss Plateau at the Beromünster tall tower. The transport model is offline coupled with the regional numerical weather prediction model (NWP) COSMO. Previous inverse modelling results for Swiss greenhouse gases are based on a model resolution of 7 km x 7 km. Here, we utilize higher resolution (1 km x 1 km) operational COSMO analysis fields to drive FLEXPART and compare these to the previous results.

The higher resolution simulations exhibit increased three-dimensional dispersion, leading to a general underestimation of observed tracer concentration at the receptor location and when compared to the coarse model results. The concentration discrepancies due to dispersion between the two model versions cannot be explained by the parameters utilized in FLEPXART’s turbulence parameterization, (Obhukov length, surface momentum and heat fluxes, atmospheric boundary layer heights, and horizontal and vertical wind speeds), since a direct comparison of these parameters between the different model versions showed no significant differences. The latter suggests that the dispersion differences may originate from a duplication of turbulent transport, on the one hand, covered by the high resolution grid of the Eulerian model and, on the other hand, diagnosed by FLEXPART's turbulence scheme. In an attempt to reconcile FLEXPART-COSMO’s turbulence scheme at high resolution, we introduced additional scaling parameters based on analysis of simulated mole fraction deviations depending on stability regime. In addition, we used FLEXPART-COSMO source sensitivities in a Bayesian inversion to obtain optimized emission estimates. Inversions for both the high and low resolution models were carried out in order to quantify the impact of model resolution on posterior emissions and estimate about the uncertainties of these emissions.  

How to cite: Katharopoulos, I., Rust, D., Vollmer, M., Brunner, D., Reimann, S., Emmenegger, L., and Henne, S.: The influence of transport model resolution on the inverse modelling of synthetic greenhouse gas emissions in Switzerland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5159,, 2020.


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displays version 1 – uploaded on 05 May 2020
  • CC1: Good work - what about FLEXPART-WRF?, Petra Seibert, 06 May 2020

    Congratulations to this very careful and interesting work!

    I am wondering what you findings mean for the WRF version of FLEXPART - WRF can be used at a wide range of grid resolutions. Thus, at, say 1 km, it might exhibit similar problems.

    Unfortunately, we don't really have a maintainer for FLEXPART-WRF at the moment. Everybody who reads this and wants to contribute to the problem w.r.t. FpWRF is invited to contact the Fp Developer Team (best through the FLEXPART mailing list, see

    • AC1: FLEXPART-WRF, Ioannis Katharopoulos, 06 May 2020

      Dear Prof Seibert,
      Firstly, I would like to thank you for your comment! I am honored.
      Personally I have never done simulations with FLEXPART driven by WRF data. In our lab we use the data provided by Meteoswiss and they use operationally the COSMO model. Recently though I have read a paper about WRF data driven simulations with different inverse modeling setups and it seems that they have the same dispersion problems with their high-resolution setups. You can find the link of the paper in the end of my answer. To answer your question, if I assume that there is not any problem with COSMO 1km fields and indeed dispersion is driven by the duplication of the turbulence by the model and the turbulence scheme then someone should notice the same problem of high dispersion in a FLEXPART-WRF simulation. I am still investigating the problem and I would come with a definite answer when I would be able to scale the turbulence scheme in a way that it is not dispersive. Thank you again for your comment!

      • AC2: Reply to AC1, Ioannis Katharopoulos, 06 May 2020