Professor Myles Allen CBE FRS

Abstract:

The relationship between cumulative CO2 emissions and CO2-induced warming is determined by the Transient Climate Response to Emissions (TCRE), but total anthropogenic warming also depends on non-CO2 forcing, complicating the interpretation of emissions budgets based on CO2 alone. An alternative is to frame emissions budgets in terms of CO2-forcing-equivalent (CO2-fe) emissions – the CO2 emissions that would yield a given total anthropogenic radiative forcing pathway. Unlike conventional ‘CO2-equivalent’ emissions, these are directly related to warming by the TCRE and need to fall to zero to stabilise warming: hence CO2-fe emissions generalise the concept of a cumulative carbon budget to multi-gas scenarios. Cumulative CO2-fe emissions from 1870-2015 inclusive are found to be 2900 ± 600GtCO2-fe, increasing at a rate of 67 ± 9.5GtCO2-fe/year. A TCRE range of 0.8–2.5° Cper 1,000 GtC implies a total budget for 0.6° C of additional warming above the present decade of 880–2,750 GtCO2-fe, with 1,290 GtCO2-fe implied by the CMIP5 median response, corresponding to 19 years' CO2-fe emissions at the current rate.

Abstract:

Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of riskbased approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900–2006), (ii) five nearfuture scenarios (2020–2049) and (iii) five far-future scenarios (2070–2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period (> 3 months) and shorter-duration high precipitation (1–30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.

Abstract:

Investors will play a major role, whether active or passive, in climate change mitigation. To enable prudent decision-making, we propose three physically based engagement principles that could be used to assess whether an investment is consistent with a long-term climate goal.

Abstract:

We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.