Summary

MAIOLICA-II: Phase 2 of the “Modeling And ExperIments On Land-surface Interactions with atmospheric Chemistry and climAte” project

Phase 2 of MAIOLICA aims to explore links between the land surface and the atmosphere focusing on the global modeling of the greenhouse gas methane (CH4). The overarching goals of MAIOLICA-II are:

  1. To improve our understanding of fundamental processes that contribute to the observed interannual and decadal variability of global atmospheric CH4 concentrations in the recent past, focusing on biospheric CH4 emissions from wetlands and fires.
  2. To investigate atmospheric CH4 in a changing climate including feedbacks among the terrestrial biosphere, atmospheric composition and climate.

MAIOLICA-II combines three different modeling approaches:

  • process-based emission modeling
  • global Lagrangian transport modeling
  • coupled chemistry-climate modeling

This approach enables an unprecedented level of understanding of processes in the CH4 cycle. The work is built upon the experiences made in MAIOLICA-I, and benefits from the close links to the recently started SNF-funded Sinergia project CarboCount-CH, which focuses on local measurements and regional modeling of CO2 and man-made CH4 emissions on the Swiss and European scale. MAIOLICA-II aimd at strong coordination with CarboCount-CH, complementing this project with the global perspective.

MAIOLICA-II consists of a number of novel modeling techniques and integrative efforts to address the objectives. A sensitivity experiment, using a combined wetland and fire emission model developed in MAIOLICA-I, will be conducted to understand the impact of variations in land cover and climate on atmospheric CH4 variability and the accumulation of CH4 in the atmosphere. A state-of-the-art atmospheric transport model and a fully coupled chemistry-climate model will be used to simulate CH4 concentrations of the recent past, covering the period 1990-2010. These simulations will be forced using the terrestrial emission fluxes from the process-based emission modeling. Intercomparison of the results from the Lagrangian model, that includes a sophisticated tracer diagnostic, with the results from the chemistry-climate model (CCM) will improve our understanding of the relative importance of feedback processes between different components of the climate system better than any single effort alone. Results from inverse modeling applied to the Lagrangian transport model will in turn be used to obtain new best estimates of wetland emissions over the investigated 20-year horizon and to validate surface processes with respect to modeled emissions distinguishing between different methane sources and geographic emission regions. This unprecedented integrated assessment, including all three modeling approaches, will provide the first comprehensive picture of how climate change and extreme climate events affect the various methane sources and sinks. The CCM will be used for future projections of atmospheric methane into the 21st century, focusing on the role of natural CH4 emissions in a changing climate. The model results will be intensively validated against various in-situ and satellite observations. Model validation and intercomparison activities will help to identify and improve model deficiencies and to provide confidence in projections of future atmospheric CH4 and the potential feedbacks with atmospheric chemistry and climate. The global chemistry-climate modeling activites will be performed in close collaboration with the recently started SNF-project FuMES, which focuses on the future role of methane in the climate system.

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