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We apply different aerosol and aerosol precursor emission scenarios reflecting possible future control strategies for air pollution in the ECHAM5-HAM model, and simulate the resulting effect on the Earth's radiation budget. We use two opposing future mitigation strategies for the year 2030: one in which emission reduction legislation decided in countries throughout the world are effectively implemented (current legislation; CLE 2030) and one in which all technical options for emission reductions are being implemented independent of their cost (maximum feasible reduction; MFR 2030). We consider the direct, semi-direct and indirect radiative effects of aerosols. The total anthropogenic aerosol radiative forcing defined as the difference in the top-of-the-atmosphere radiation between 2000 and pre-industrial times amounts to −2.00 W/m2. In the future this negative global annual mean aerosol radiative forcing will only slightly change (+0.02 W/m2) under the "current legislation" scenario. Regionally, the effects are much larger: e.g. over Eastern Europe radiative forcing would increase by +1.50 W/m2 because of successful aerosol reduction policies, whereas over South Asia it would decrease by −1.10 W/m2 because of further growth of emissions. A "maximum feasible reduction" of aerosols and their precursors would lead to an increase of the global annual mean aerosol radiative forcing by +1.13 W/m2. Hence, in the latter case, the present day negative anthropogenic aerosol forcing could be more than halved by 2030 because of aerosol reduction policies and climate change thereafter will be to a larger extent be controlled by greenhouse gas emissions. We combined these two opposing future mitigation strategies for a number of experiments focusing on different sectors and regions. In addition, we performed sensitivity studies to estimate the importance of future changes in oxidant concentrations and the importance of the aerosol microphysical coupling within the range of expected future changes. For changes in oxidant ...

The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over two decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. Here we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copy-right work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce, or limit each other.