Oral or Poster

IAMAS

M01 - Atmospheric Chemistry in the Anthropocene: From the Urban to Global Scales

Hindcasting simulation of global methane concentration with a Chemistry Climate Model

There are high expectations for reducing emissions of methane (CH4), which has the second largest radiative forcing after carbon dioxide, to mitigate climate change. Atmospheric CH4 concentration is governed not only by emissions, but by atmospheric transport and chemical reactions, therefore, even if CH4 emissions are reduced, it is not easy to quantitatively evaluate to what extent CH4 concentrations will decrease and to what extent temperature rise will be mitigated. Chemistry-Climate Model (CCM) is an essential tool for scientifically approaching these important issues. However, in most of the studies to evaluate the climate impact of CH4 changes, calculations have been performed by specifying the CH4 concentration in the model (concentration-driven experiments), and only a limited number of studies have been performed to directly evaluate the effect of emission reductions on the climate by inputting CH4 emissions to CCM and calculating CH4 concentrations in the model (emission-driven calculations). We are working on directly evaluating the climate impact of CH4 emission changes by performing emission-driven simulations using a global-scale CCM. Here, we report the results of simulations to reproduce past CH4 concentrations driven by CH4 emission changes from pre-industrial (PI) era (1850) to the present (2014). We first evaluated the emissions that would reproduce the estimated global surface CH4 concentration in the PI era of ~800 ppbv, and obtained a value of approximately 163 TgCH4/yr. Then, we fed the model historical changes in sea surface temperature (SST) and sea ice, increased anthropogenic CH4 emissions from fossil fuels, agriculture, waste management and so on toward the present, and calculated the changes in atmospheric CH4 concentration. The model was able to reproduce the observed increase in concentration well. However, after the 1970s, the model tends to underestimate the observed concentrations (up to about 100 ppbv). From the observation, it is known that there are large interannual variations in the rate of change in CH4 concentration, and it is known that the increasing rate in CH4 concentration slowed down toward the early 2000s before increasing again, and the model used able to capture this characteristic well. In a sensitivity simulation in which the SST and sea ice were kept in the PI state and no climate change such as global warming was forced, the surface concentration of CH4 increased by up to 4% compared to when climate change was applied. Conversely, this suggests that past climate change had the effect of reducing CH4 concentrations.