Methane simulations at Cape Grim to assess methane flux estimates for South East Australia

Abstract

A transport model intercomparison for methane (TransCom-CH4) has been run involving twelve models (Patra et al., 2011). We contributed simulations using two climate models, CCAM and ACCESS. The CCAM simulations were nudged to NCEP analysed meteorology, which allows simulated atmospheric concentrations to be compared to observations on synoptic timescales. The ACCESS simulations were forced only with observed sea surface temperatures and are consequently not expected to match observed synoptic variations. The TransCom experiment involved simulating six CH4 tracers (with different prescribed fluxes) along with SF6, radon and methyl chloroform. We have analysed hourly model output for Cape Grim and find that the magnitude of the non-baseline signal differs, especially in winter, dependent on the CH4 flux scenario used. The magnitude of the non-baseline signal also varies between models, although these differences can be reconciled when methane is scaled by model-simulated radon concentration. Comparison with observed CH4, also scaled using radon, suggests that the CH4 flux scenario with little or no wetland emissions in winter matches the observations. The observations also indicate an apparent extra source of CH4 in October-November not seen in the model simulations. However this appears to be an artefact of this analysis method which assumes that radon emissions are known (and in this case constant in space and time). We have found that the discrepancy between model and observations in spring appears to be due to a poor simulation of radon, rather than CH4. Observed radon shows a larger seasonality than modelled radon, which suggests that temporal and spatial variations in radon flux need to be considered. It would also be helpful to understand why the simulated CCAM and ACCESS radon (and non-baseline CH4) concentrations differ in magnitude. Comparisons with Cape Grim output from the other participating TransCom-CH4 models may provide some insight