Methane chemistry in a nutshell – The new submodels CH4 (v1.0) and TRSYNC (v1.0) in MESSy (v2.54.0) [post]

Franziska Winterstein, Patrick Jöckel
2020 unpublished
Abstract. Climate projections including chemical feedbacks rely on state-of-the-art chemistry-climate models (CCMs). Of particular importance is the role of methane (CH4) for the budget of stratospheric water vapor (SWV), which has an important climate impact. However, simulations with CCMs are, due to the large number of involved chemical species, computationally demanding, which limits the simulation of sensitivity studies. To allow for sensitivity studies and ensemble simulations with a
more » ... lations with a reduced demand for computational resources, we introduce a simplified approach to simulate the core of methane chemistry in form of the new Modular Earth Submodel System (MESSy) submodel CH4. It involves an atmospheric chemistry mechanism reduced to the sink reactions of CH4 with predefined fields of the hydroxyl radical (OH), excited oxygen (O(1D)), and chlorine (Cl), as well as photolysis and the reaction products limited to water vapour (H2O). This chemical production of H2O is optionally feed back onto the specific humidity (q) of the connected General Circulation Model (GCM), to account for the impact onto SWV and its effect on radiation and stratospheric dynamics. The submodel CH4 is further capable of simulating the four most prevalent CH4 isotopologues for carbon and hydrogen (CH4 and CH3D as well as 12CH4 and 13CH4), respectively. Furthermore, the production of deuterated water vapour (HDO) is, similar to the production of H2O in the CH4 oxidation, optionally feed back to the isotopological hydrological cycle simulated by the submodel H2OISO, using the newly developed auxiliary submodel TRSYNC. Moreover, the simulation of a user defined number of diagnostic CH4 age- and emission classes is possible, which output can be used for offline inverse optimization techniques. The presented approach combines the most important chemical hydrological feedback including the isotopic signatures with the advantages concerning the computational simplicity of a GCM, in comparison to a full featured CCM.
doi:10.5194/gmd-2020-137 fatcat:xb6pygjdprdwxbkxjzsxxl3lra