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Abstract:

Limiting global warming to 1.5 or 2.0 °C requires strong mitigation of anthropogenic greenhouse gas (GHG) emissions. Concurrently, emissions of anthropogenic aerosols will decline, due to co-emission with GHG, and measures to improve air quality. However, the combined climate effect of GHG and aerosol emissions over the industrial era is poorly constrained. Here we show the climate impacts from removing present day anthropogenic aerosol emissions, and compare them to the impacts from moderate GHG dominated global warming. Removing aerosols induces a global mean surface heating of 0.5-1.1 °C, and precipitation increase of 2.0-4.6 %. Extreme weather indices also increase. We find a higher sensitivity of extreme events to aerosol reductions, per degree of surface warming, in particular over the major aerosol emission regions. Under near term warming, we find that regional climate change will depend strongly on the balance between aerosol and GHG forcing.

Abstract:

Using a simple pedagogical model, it is shown how information about the statistical reliability of initial-value ensemble forecasts can be relevant in assessing the trustworthiness of the climate system’s response to forcing.

Although the development of seamless prediction systems is becoming increasingly common, there is still confusion regarding the relevance of information from initial-value forecasts for assessing the trustworthiness of the climate system’s response to forcing. A simple system which mimics the real climate system through its regime structure is used to illustrate this potential relevance. The more complex version of this model defines “REALITY” and a simplified version of the system represents the “MODEL”. The MODEL’s response to forcing is profoundly incorrect. However, the untrustworthiness of the MODEL’s response to forcing can be deduced from the MODEL’s initial-value unreliability. The nonlinearity of the system is crucial in accounting for this result.