Radiative Forcing Bias Calculation Based on COSMO (Core-Shell Mie model Optimization) and AERONET data

Abstract

Abstract Direct radiative forcing (DRF) of aerosols is driven by aerosol concentration, size, and mixing state, and solar radiation. This work introduces Core-Shell Mie model optimization(COSMO) to compute top of the atmosphere (TOA) forcing based on inversely constrained BC size and mixing state from AERONET, over two rapidly developing areas: Lumbini and Taihu. COSMO has wider variability and less negative TOA than AERONET (13.0 ± 8.1 Watt/m2 at Lumbini and 15.6 ± 12.4 Watt/m2 at Taihu). These differences are driven by particle aging and size-resolved BC emissions, with up to 17.9% of cases warmer than the maximum AERONET TOA, and 1.9% net-warming. A linearized correction is deduced which can be immediately implemented by climate models, and suggested ranges of BC size- and mixing- observations are made for future campaigns. Given that the COSMO TOA bias and uncertainty are larger than the forcing of locally emitted GHGs, active consideration of BC is necessary to reduce climate uncertainty in developing areas.