Adjoint inverse modeling of black carbon during the Asian Pacific Regional Aerosol Characterization Experiment

Abstract

An adjoint model is used for inverse modeling of black carbon during the Asian Pacific Regional Aerosol Characterization Experiment (ACE‐Asia). We use the four‐dimensional variational data assimilation (4D‐Var) approach to optimally recover spatially resolved anthropogenic and biomass‐burning emissions and initial and boundary conditions of black carbon. Boundary conditions and biomass‐burning emissions are assigned daily scaling factors. Anthropogenic emissions are scaled by a combination of daily and monthly scaling factors. Simulation results are compared to various observations of black carbon concentrations during the campaign. Measurements at five islands and on board the research vessel Ronald H. Brown are used for inverse modeling. Different levels of constraints are examined for inversion, and a case with 62% reduction in the total square errors is chosen. The assimilated results are compared with the observations on board the Twin Otter aircraft that were not used for assimilation. Among the scaled variables, anthropogenic emissions are the most significant, followed by the boundary conditions. The domain‐wide emissions inventory does not change significantly as a result of the assimilation, but sizable changes occur on the subregional level. Most noticeably, anthropogenic emissions over southeastern China are reduced while those in northeast China and Japan are increased.