A revised dry deposition scheme for land-atmosphere exchange of trace gases in ECHAM/MESSy v2.543

Tamara Emmerichs is a Doctoral Researcher at the Institute of Energy and Climate Research (Troposphere) at the Forschungszentrum Jülich. She was one of the 50 students attending the ESM Summer School in 2019 in Bad Aibling. Her work focuses on chemical processes influencing interactions between pollution and weather, with special focus on the development of the dry deposition representation in the atmospheric chemistry model ECHAM/MESSy. She tells us more about it in this article.

One relevant loss process for atmospheric gases is dry deposition where the compounds are transported to the surface and deposit there. In particular for ground-level ozone, the uptake to vegetation plays an important role responsible for 20 % of the total loss of tropospheric ozone. Tropospheric ozone is a secondary produced air pollutant harmful for humans and plants which plays an important role for the tropospheric chemistry. Therefore, an accurate representation in models is important. However, most chemistry models show an overestimation of tropospheric ozone with respect to observations. Thereby, the parametrization of dry deposition to vegetation represents a major source of uncertainty for the global tropospheric ozone budget and might account for this mismatch with observations. The global numerical chemistry and climate simulation system used in this study, the Modular Earth Submodel System (MESSy2 - www.messy-interface.org) linked to ECHAM5 as atmospheric circulation model (EMAC), is no exception. The simulation system describes atmospheric processes in the lower and middle atmosphere and their interaction with ocean, land and human influences.

Like many global models, EMAC employs a “resistances in series” scheme within the dry deposition submodel where each resistor represents one compartment considered for the uptake of trace gases. The major surface deposition occurs via plant pores (stomata) which is hardly sensitive to meteorology depending only on solar radiation and thus lacks important dependencies according to the current knowledge. For non-stomatal deposition, however, EMAC uses a simplified high resistance which makes this pathway negligible.

Hence, in this study, the parametrization of ozone dry deposition has been revised based on established schemes. We applied two empirical adjustment factors to predict stomatal responses to temperature and vapour pressure deficit. This enables stomata to react to weather extremes which become more frequent with climate warming. A further development is the implementation of an explicit formulation of the uptake at leaf surfaces (cuticle) which depends on surface wetness, humidity and vegetation density. Next, the soil moisture availability function for plants, which control the stomatal response to the available soil moisture in the model, has been critically reviewed. In regions where the model shows a strong soil dry bias, e.g. Amazon basin in dry season, the function has been modified in order to avoid stomatal closure.

The modifications increase the global dry deposition flux of ozone by 6 % which leads to less ground-level ozone, regionally up to 20 %. This change arises mainly from the inclusion of cuticular uptake which is favourable at moist and humid surfaces. The impact on stomatal uptake varies in sign and magnitude dependent on local meteorology whereas the temperature stress factor dampens the stomatal uptake and the drought factor led to a more dominant and various response.

Comparing simulated dry deposition velocities and fluxes with data at four experimental sites, where ozone deposition is measured with micrometeorological techniques, give further insights to the local different mechanisms. Overall, the comparison shows a more realistic representation of ozone dry deposition regarding the revised scheme limited by the simulated local meteorology. These changes might contribute to an improved model representation of tropospheric ozone and lower the mismatch with observations.

You can read the whole paper here: Emmerichs, T., Kerkweg, A., Ouwersloot, H., Fares, S., Mammarella, I., and Taraborrelli, D. (2021): A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54, Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021.

We asked Tamara some updates on her current work and about doing research in Corona times. here are her answers:

How did the experience in the ESM summer school help you with your work and career?

The lectures on the different parts of the Earth system broadened my knowledge apart from my university studies in atmospheric sciences. The exchange with the other students opened up new perspectives on science and ideas.

What are you currently working on?

Making use of model developments regarding the sensitivity of ground-level ozone to meteorology and the land-atmosphere exchange of ozone and it’s precursors like the one described above I compare global EMAC simulations with measurements from different sources.

How has COVID-19 changed your working situation?

My workplace has been always at home since the pandemic began. This makes the communication and information exchange sometimes more difficult. Also the spontaneous chats with colleagues during lunch time, for example, are missing.

How would you describe your job or reasearch to an eight year old?

What surrounds all of us is air. The air changes its composition frequently. By thousands of reactions where air compounds like water vapor bump, combine and modify each other the concentration of these compounds’ changes. The compounds are emitted by plants but also by human processes like cars and industry. After some time, they are removed again by rain or uptake on plants. This impacts not only the quality of the air we are breathing; it also can influence the weather. To get a better understanding of these processes and be able to predict how the change the atmosphere composition we imagine the whole Earth can be divided in boxes. In each of the boxes we can represent the different reactions between air compounds, the emission and removal processes. However, what we model is often not the same what we see in the real world. We constantly try to improve our process understanding and include this in our model.