Jason Lowe

Warming caused by cumulative carbon emissions towards the trillionth tonne

Global efforts to mitigate climate change are guided by projections of future temperatures. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions. Here we use ensemble simulations of simple climate-carbon-cycle models constrained by observations and projections from more comprehensive models to simulate the temperature response to a broad range of carbon dioxide emission pathways. We find that the peak warming caused by a given cumulative carbon dioxide emission is better constrained than the warming response to a stabilization scenario. Furthermore, the relationship between cumulative emissions and peak warming is remarkably insensitive to the emission pathway (timing of emissions or peak emission rate). Hence policy targets based on limiting cumulative emissions of carbon dioxide are likely to be more robust to scientific uncertainty than emission-rate or concentration targets. Total anthropogenic emissions of one trillion tonnes of carbon (3.67 trillion tonnes of CO2), about half of which has already been emitted since industrialization began, results in a most likely peak carbon-dioxide-induced warming of 2 °C above pre-industrial temperatures, with a 5–95% confidence interval of 1.3–3.9 °C.

The New Hadley Centre Climate Model (HadGEM1): Evaluation of Coupled Simulations

Abstract A new coupled general circulation climate model developed at the Met Offices Hadley Centre is presented, and aspects of its performance in climate simulations run for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) documented with reference to previous models. The Hadley Centre Global Environmental Model version 1 (HadGEM1) is built around a new atmospheric dynamical core; uses higher resolution than the previous Hadley Centre model, HadCM3; and contains several improvements in its formulation including interactive atmospheric aerosols (sulphate, black carbon, biomass burning, and sea salt) plus their direct and indirect effects. The ocean component also has higher resolution and incorporates a sea ice component more advanced than HadCM3 in terms of both dynamics and thermodynamics. HadGEM1 thus permits experiments including some interactive processes not feasible with HadCM3. The simulation of present-day mean climate in HadGEM1 is significantly better overall ...

Sea-level rise and its possible impacts given a ‘beyond 4°C world’ in the twenty-first century

The range of future climate-induced sea-level rise remains highly uncertain with continued concern that large increases in the twenty-first century cannot be ruled out. The biggest source of uncertainty is the response of the large ice sheets of Greenland and west Antarctica. Based on our analysis, a pragmatic estimate of sea-level rise by 2100, for a temperature rise of 4°C or more over the same time frame, is between 0.5 m and 2 m—the probability of rises at the high end is judged to be very low, but of unquantifiable probability. However, if realized, an indicative analysis shows that the impact potential is severe, with the real risk of the forced displacement of up to 187 million people over the century (up to 2.4% of global population). This is potentially avoidable by widespread upgrade of protection, albeit rather costly with up to 0.02 per cent of global domestic product needed, and much higher in certain nations. The likelihood of protection being successfully implemented varies between regions, and is lowest in small islands, Africa and parts of Asia, and hence these regions are the most likely to see coastal abandonment. To respond to these challenges, a multi-track approach is required, which would also be appropriate if a temperature rise of less than 4°C was expected. Firstly, we should monitor sea level to detect any significant accelerations in the rate of rise in a timely manner. Secondly, we need to improve our understanding of the climate-induced processes that could contribute to rapid sea-level rise, especially the role of the two major ice sheets, to produce better models that quantify the likely future rise more precisely. Finally, responses need to be carefully considered via a combination of climate mitigation to reduce the rise and adaptation for the residual rise in sea level. In particular, long-term strategic adaptation plans for the full range of possible sea-level rise (and other change) need to be widely developed.

Elimination of the greenland Ice sheet in a high CO2 climate

Projections of future global sea level depend on reliable estimates of changes in the size of polar ice sheets. Calculating this directly from global general circulation models (GCMs) is unreliable because the coarse resolution of 100 km or more is unable to capture narrow ablation zones, and ice dynamics is not usually taken into account in GCMs. To overcome these problems a high-resolution (20 km) dynamic ice sheet model has been coupled to the third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). A novel feature is the use of two-way coupling, so that climate changes in the GCM drive ice mass changes in the ice sheet model that, in turn, can alter the future climate through changes in orography, surface albedo, and freshwater input to the model ocean. At the start of the main experiment the atmospheric carbon dioxide concentration was increased to 4 times the preindustrial level and held constant for 3000 yr. By the end of this period the Greenland ice sheet is almost completely ablated and has made a direct contribution of approximatel y7mt oglobal average sea level, causing a peak rate of sea level rise of 5 mm yr 1 early in the simulation. The effect of ice sheet depletion on global and regional climate has been examined and it was found that apart from the sea level rise, the long-term effect on global climate is small. However, there are some significant regional climate changes that appear to have reduced the rate at which the ice sheet ablates.

When could global warming reach 4°C?

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate–carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with ‘FI’ standing for ‘fossil intensive’. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC’s ‘likely range’.

The effects of climate change on storm surges around the United Kingdom

Coastal flooding is often caused by extreme events, such as storm surges. In this study, improved physical models have been used to simulate the climate system and storm surges, and to predict the effect of increased atmospheric concentrations of greenhouse gases on the surges. In agreement with previous studies, this work indicates that the changes in atmospheric storminess and the higher time-average sea-level predicted for the end of the twenty-first century will lead to changes in the height of water levels measured relative to the present day tide. However, the details of these projections differ somewhat from earlier assessments. Uncertainty in projections of future extreme water levels arise from uncertainty in the amount and timing of future greenhouse gas emissions, uncertainty in the physical models used to simulate the climate system and from the natural variability of the system. The total uncertainty has not yet been reliably quantified and achieving this should be a priority for future research.

Overshoot, adapt and recover.

We will probably overshoot our current climate targets, so policies of adaptation and recovery need much more attention, say Martin Parry, Jason Lowe and Clair Hanson.

Transient Climate Simulations with the HadGEM1 Climate Model: Causes of Past Warming and Future Climate Change

The ability of climate models to simulate large-scale temperature changes during the twentieth century when they include both anthropogenic and natural forcings and their inability to account for warming over the last 50 yr when they exclude increasing greenhouse gas concentrations has been used as evidence for an anthropogenic influence on global warming. One criticism of the models used in many of these studies is that they exclude some forcings of potential importance, notably from fossil fuel black carbon, biomass smoke, and land use changes. Herein transient simulations with a new model, the Hadley Centre Global Environmental Model version 1 (HadGEM1), are described, which include these forcings in addition to other anthropogenic and natural forcings, and a fully interactive treatment of atmospheric sulfur and its effects on clouds. These new simulations support previous work by showing that there was a significant anthropogenic influence on near-surface temperature change over the last century. They demonstrate that black carbon and land use changes are relatively unimportant for explaining global mean near-surface temperature changes. The pattern of warming in the troposphere and cooling in the stratosphere that has been observed in radiosonde data since 1958 can only be reproduced when the model includes anthropogenic forcings. However, there are some discrepancies between the model simulations and radiosonde data, which are largest where observational uncertainty is greatest in the Tropics and high latitudes. Predictions of future warming have also been made using the new model. Twenty-first-century warming rates, following policy-relevant emissions scenarios, are slightly greater in HadGEM1 than in the Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3) as a result of the extra forcing in HadGEM1. An experiment in which greenhouse gases and other anthropogenic forcings are stabilized at 2100 levels and held constant until 2200 predicts a committed twenty-second-century warming of less than 1 K, whose spatial distribution resembles that of warming during the twenty-first century, implying that the local feedbacks that determine the pattern of warming do not change significantly.

Climate change and heat-related mortality in six cities Part 2: Climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change.

Previous assessments of the impacts of climate change on heat-related mortality use the “delta method” to create temperature projection time series that are applied to temperature–mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heat-related mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature–mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heat-related mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

Dispersion, deposition and impacts of atmospheric ammonia: quantifying local budgets and spatial variability

Ammonia is a reactive pollutant emitted primarily by agricultural sources near ground level in the rural environment. The consequence of these factors is that, in addition to the effects of long-range pollutant transport, ammonia has major effects at a local scale, with emission and receptor areas often closely located in the rural landscape. There is a substantial local spatial variability that needs to be considered in effects assessments, while variations in local deposition may affect the amount of ammonia available for impacts further afield. The wide-ranging UK programme ADEPT (Ammonia Distribution and Effects ProjecT) has addressed these issues through a combination of measurement and modelling activities concerning the distribution of emissions, atmospheric transport, deposition and effects assessment. The results are illustrated here by summarizing the findings of a joint experiment at Burrington Moor, Devon, and wider modelling contrasting the variability at a field scale with 5 km resolution estimates for the UK. The fraction of emitted NH3 deposited locally is shown to depend critically on the downwind land-cover, with fluxes being dependent on interactions with the ammonia compensation point. This will restrict deposition back to agricultural land, but may mean that non-conservation woodlands could be of benefit to recapture a significant fraction of emissions. The generalized models demonstrate the high spatial variability of ammonia impacts, with a case study being used to show the consequences at a field scale. In source regions substantial variability occurs at sub-1 km levels and this will have major consequences for the emission reduction targets needed to protect ecosystems.