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The United Nations' Paris Agreement includes the aim of pursuing efforts to limit global warming to only 1.5 °C above pre-industrial levels. However, it is not clear what the resulting climate would look like across the globe and over time. Here we show that trajectories towards a '1.5 °C warmer world' may result in vastly different outcomes at regional scales, owing to variations in the pace and location of climate change and their interactions with society's mitigation, adaptation and vulnerabilities to climate change. Pursuing policies that are considered to be consistent with the 1.5 °C aim will not completely remove the risk of global temperatures being much higher or of some regional extremes reaching dangerous levels for ecosystems and societies over the coming decades.The results of efforts to limit global mean warming to below 1.5 °C may include many possible future world climates., Author(s): Sonia I. Seneviratne [sup.1] , Joeri Rogelj [sup.1] [sup.2] [sup.3] [sup.4] , Roland Séférian [sup.5] , Richard Wartenburger [sup.1] , Myles R. Allen [sup.3] , Michelle Cain [sup.3] , [...]

Many developments have taken place within dataflow programming languages in the past decade. In particular, there has been a great deal of activity and advancement in the field of dataflow visual programming languages. The motivation for this article is to review the content of these recent developments and how they came about. It is supported by an initial review of data flow programming in the 1970s and 1980s that led to current topics of research. It then discusses how dataflow programming evolved toward a hybrid von Neumann dataflow formulation, and adopted a more coarse-grained approach. Recent trends toward dataflow visual programming languages are then discussed with reference to key graphical dataflow languages and their development environments. Finally, the article details four key open topics in dataflow programming languages. Categories and Subject Descriptors: A.1 [Introductory and Survey]; C.1 [Processor Architectures]; D.2 [Software Engineering]; D.3 [Programming Languages] General Terms: Languages, Theory Additional Key Words and Phrases: Dataflow, software engineering, graphical programming, component software, multithreading, co-ordination languages, data flow visual programming

Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone precursors and other agents. The ERFs are integrated into global mean surface temperature change. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. For the historical period the ERF time series in FAIR emulates the results in the IPCC Fifth Assessment Report (AR5), whereas for RCP historical and future scenarios, the greenhouse gas concentrations in FAIR closely track the observations and projections in the RCPs. The constrained estimates of equilibrium climate sensitivity (ECS) of 2.79 (1.97 to 4.08) K, transient climate response (TCR) of 1.47 (1.03 to 2.23) K and transient climate response to cumulative CO2 emissions (TCRE) of 1.43 (1.01 to 2.16) K (1000 GtC)-1 (median and 5-95 % credible intervals) are in good agreement, with tighter uncertainty bounds, than AR5 (1.5 to 4.5 K, 1.0 to 2.5 K, and 0.8 to 2.5 K respectively). The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are moderately sensitive to the historical temperature dataset used to constrain, prior distributions of ECS/TCR parameters, aerosol radiative forcing relationship and ERF from a doubling of CO2. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. However, the range of temperature projections under the RCP scenarios for 2081-2100 in the constrained FAIR model ensemble are lower than the emissions-based estimates reported in AR5. [ABSTRACT FROM AUTHOR]

Projections of the response to anthropogenic emission scenarios, evaluation of some greenhouse gas metrics and estimates of the social cost of carbon, often require a simple model that links emissions of carbon dioxide CO2 to atmospheric concentrations and global temperature changes. An essential requirement of such a model is to reproduce the behaviour of more complex models as well as an ability to sample their range of response in a transparent, accessible and reproducible form. Here we adapt the simple model of the Intergovernmental Panel on Climate Change 5th Assessment Report (IPCC-AR5) to explicitly represent the state-dependence of the CO2 airborne fraction and reproduce several idealised experiments performed with more complex models. We find that a simple linear increase in 100-year integrated airborne fraction with cumulative carbon uptake and global temperature change is both necessary and sufficient to represent the response of the climate system to CO2 on a range of timescales and under a range of experimental designs. Quantified ranges of uncertainty (analogous to current assessed ranges in Equilibrium Climate Sensitivity and Transient Climate Response) in integrated airborne fraction over the 21st century under a representative mitigation scenario, and an assessed range in how much this quantity may have changed relative to pre-industrial conditions, would be valuable in future scientific assessments. [ABSTRACT FROM AUTHOR]

While cumulative carbon dioxide (CO2) emissions dominate anthropogenic warming over centuries, temperatures over the coming decades are also strongly affected by short-lived climate pollutants (SLCPs), complicating the estimation of cumulative emission budgets for ambitious mitigation goals. Using conventional Global Warming Potentials (GWPs) to convert SLCPs to "CO2-equivalent" emissions misrepresents their impact on global temperature. Here we show that peak warming under a range of mitigation scenarios is determined by a linear combination of cumulative CO2 emissions to the time of peak warming and non-CO2 radiative forcing immediately prior to that time. This may be understood by expressing aggregate non-CO2 forcing as cumulative CO2 forcing-equivalent (CO2-fe) emissions. We show further that contributions to CO2-fe emissions are well approximated by a new usage of GWP, denoted GWP*, which relates cumulative CO2 emissions to date with the current rate of emission of SLCPs. GWP* accurately indicates the impact of emissions of both long-lived and short-lived pollutants on radiative forcing and temperatures over a wide range of timescales, including under ambitious mitigation when conventional GWPs fail. Measured by GWP*, implementing the Paris Agreement would reduce the expected rate of warming in 2030 by 28% relative to a No Policy scenario. Expressing mitigation efforts in terms of their impact on future cumulative emissions aggregated using GWP* would relate them directly to contributions to future warming, better informing both burden-sharing discussions and long-term policies and measures in pursuit of ambitious global temperature goals. Climate mitigation: An improved emission metric A new approach allows the temperature forcing of CO2 and short-lived climate pollutants (SLCPs) to be examined under a common cumulative framework. While anthropogenic warming is largely determined by cumulative emissions of CO2, SLCPs—including soot, other aerosols and methane—also play a role. Quantifying their impact on global temperature is, however, distorted by existing methodologies using conventional Global Warming Potentials (GWP) to convert SLCPs to "CO2-equivalent" emissions. A team of international scientists led by Myles Allen at the University of Oxford provide a solution. A modified form of GWP—GWP*, which relates cumulative CO2 emissions with contemporary SLCP emissions—is shown to better represent the future climate forcing of both long- and short-term pollutants. Use of GWP* could improve climate policy design, benefiting mitigation strategies to achieve the Paris Agreement targets. [ABSTRACT FROM AUTHOR]

The historical observational record offers a way to constrain the relationship between cumulative carbon dioxide emissions and global mean warming. We use a standard detection and attribution technique, along with observational uncertainties to estimate the all-forcing or 'effective' transient climate response to cumulative emissions (TCRE) from the observational record. Accounting for observational uncertainty and uncertainty in historical non-CO 2 radiative forcing gives a best-estimate from the historical record of 1.84°C/TtC (1.43-2.37°C/TtC 5-95% uncertainty) for the effective TCRE and 1.31°C/TtC (0.88-2.60°C/TtC 5-95% uncertainty) for the CO 2 -only TCRE. While the best-estimate TCRE lies in the lower half of the IPCC likely range, the high upper bound is associated with the not-ruled-out possibility of a strongly negative aerosol forcing. Earth System Models have a higher effective TCRE range when compared like-for-like with the observations over the historical period, associated in part with a slight underestimate of diagnosed cumulative emissions relative to the observational best-estimate, a larger ensemble mean-simulated CO 2 -induced warming, and rapid post-2000 non-CO 2 warming in some ensemble members.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'., (© 2018 The Authors.)