New use of global warming potentials to compare cumulative and short-lived climate pollutants
Nature Climate Change Nature Publishing Group (2016)
Abstract:
Parties to the United Nations Framework Convention on Climate Change (UNFCCC) have requested guidance on common greenhouse gas metrics in accounting for Nationally determined contributions (NDCs) to emission reductions1. Metric choice can affect the relative emphasis placed on reductions of ‘cumulative climate pollutants’ such as carbon dioxide versus ‘short-lived climate pollutants’ (SLCPs), including methane and black carbon2, 3, 4, 5, 6. Here we show that the widely used 100-year global warming potential (GWP100) effectively measures the relative impact of both cumulative pollutants and SLCPs on realized warming 20–40 years after the time of emission. If the overall goal of climate policy is to limit peak warming, GWP100 therefore overstates the importance of current SLCP emissions unless stringent and immediate reductions of all climate pollutants result in temperatures nearing their peak soon after mid-century7, 8, 9, 10, which may be necessary to limit warming to “well below 2 °C” (ref. 1). The GWP100 can be used to approximately equate a one-off pulse emission of a cumulative pollutant and an indefinitely sustained change in the rate of emission of an SLCP11, 12, 13. The climate implications of traditional CO2-equivalent targets are ambiguous unless contributions from cumulative pollutants and SLCPs are specified separately.Attribution of extreme weather events in Africa: a preliminary exploration of the science and policy implications
CLIMATIC CHANGE 132:4 (2015) 531-543
Abstract:
© 2015 The Author(s) Extreme weather events are a significant cause of loss of life and livelihoods, particularly in vulnerable countries and communities in Africa. Such events or their probability of occurring may be, or are, changing due to climate change with consequent changes in the associated risks. To adapt to, or to address loss and damage from, this changing risk we need to understand the effects of climate change on extreme weather events and their impacts. The emerging science of probabilistic event attribution can provide scientific evidence about the contribution of anthropogenic climate change to changes in risk of extreme events. This research has the potential to be useful for climate change adaptation, but there is a need to explore its application in vulnerable developing countries, particularly those in Africa, since the majority of existing event attribution studies have focused on mid-latitude events. Here we explain the methods of, and implications of, different approaches to attributing extreme weather events in an African context. The analysis demonstrates that different ways of framing attribution questions can lead to very different assessments of change in risk. Crucially, defining the most appropriate attribution question to ask is not a science decision but one that needs to be made in dialogue with those stakeholders who will use the answers. This is true of all attribution studies but may be particularly relevant in a tropical context, suggesting that collaboration between scientists and policy-makers is a priority for Africa.Embracing uncertainty in climate change policy
Nature Climate Change Springer Nature 5:10 (2015) 917-920
Towards a typology for constrained climate model forecasts
Climatic Change 132:1 (2015) 15-29
Abstract:
In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context.Attribution analysis of high precipitation events in summer in England and Wales over the last decade
Climatic Change Springer Nature 132:1 (2015) 77-91