Inverse estimation for the simple earth system model ACC2 and its applications

Abstract

The Aggregated Carbon Cycle, Atmospheric Chemistry, and Climate model (ACC2) (Tanaka and Kriegler et al., 2007a) describes physical-biogeochemical processes in the Earth system at a global-annual-mean level. Compared to its predecessors NICCS (Hooss, 2001) and ICM (Bruckner et al., 2003), ACC2 adopts more detailed parameterizations of atmospheric chemistry involving a set of agents (CO2, CH4, N2O, O3, SF6, 29 species of halocarbons, sulfate aerosols (direct effect), carbonaceous aerosols (direct effect), all aerosols (indirect effect), stratospheric H2O, OH, and pollutants NOx, CO, and VOC). In contrast to the Impulse Response Function (IRF) approaches in the predecessor models, ACC2 uses DOECLIM (Kriegler, 2005), a land-ocean Energy Balance Model (EBM), to calculate temperature change. The carbon cycle is described by box models based on the IRF approach. A temperature feedback is newly implemented to ocean and land CO2 uptake. The most novel aspect of ACC2 is its inverse estimation, the first attempt to estimate uncertain parameters simultaneously for the carbon cycle, atmospheric chemistry, and climate system by taking their interactions into account. Theoretical underpinning of the ACC2 inversion is the probabilistic inverse estimation theory (Tarantola, 2005), which characterizes the ACC2 inversion as an integration of the existing Earth system knowledge. This includes parameter estimates, observational databases, reconstructions, and physical-biogeochemical laws...