For geographers engaged in activities such as environmental planning and natural resource management, regional climate models are becoming increasingly important as a source of information about the possible impacts of future climate change. However, in order to make informed adaptation decisions, the uncertainties associated with their output must be recognized and taken into account. In this paper, the cascade of uncertainty from emissions scenario to global model to regional climate model is explored. The initial part of the discussion focuses on uncertainties associated with human action, such as emissions of greenhouse gases, and the climate system’s response to increased greenhouse gas forcing, which includes climate sensitivity and feedbacks. In the second part of the discussion, uncertainties associated with climate modelling are explored with emphasis on the implications for regional scale analysis. Such uncertainties include parameterizations and resolutions, initial and boundary conditions inherited from the driving global model, intermodel variability and issues surrounding the validation or verification of models. The paper concludes with a critique of approaches employed to quantify or cater for uncertainties highlighting the strengths and limitations of such approaches.

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This paper presents an analysis of climate policy instruments for the decarbonisation of the global electricity sector in a non-equilibrium economic and technology diffusion perspective. Energy markets are driven by innovation, pathdependent technology choices and diffusion. However, conventional optimisation models lack detail on these aspects and have limited ability to address the effectiveness of policy interventions because they do not represent decision-making. As a result, known effects of technology lock-ins are liable to be underestimated. In contrast, our approach places investor decision-making at the core of the analysis and investigates how it drives the diffusion of low-carbon technology in a highly disaggregated, hybrid, global macroeconometric model, FTT:Power-E3MG. Ten scenarios to 2050 of the electricity sector in 21 regions exploring combinations of electricity policy instruments are analysed, including their climate impacts. We show that in a diffusion and path-dependent perspective, the impact of combinations of policies does not correspond to the sum of impacts of individual instruments: synergies exist between policy tools. We argue that the carbon price required to break the current fossil technology lock-in can be much lower when combined with other policies, and that a 90% decarbonisation of the electricity sector by 2050 is affordable without early scrapping.

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Objective Health systems make a sizeable contribution to national emissions of greenhouse gases that contribute to global climate change. The UK National Health Service is committed to being a net zero emitter by 2040, and a potential contribution to this target could come from reductions in patient travel. Achieving this will require actions at many levels. We sought to determine potential savings and risks over the short term from telemedicine through virtual clinics. Methods During the severe acute respiratory syndrome coronavirus 2 (SARS‐2‐CoV) pandemic, scheduled face‐to‐face epilepsy clinics at a specialist site were replaced by remote teleclinics. We used a standard methodology applying conversion factors to calculate emissions based on the total saved travel distance. A further conversion factor was used to derive emissions associated with electricity consumption to deliver remote clinics from which net savings could be calculated. Patients’ records and clinicians were interrogated to identify any adverse clinical outcomes. Results We found that enforced telemedicine delivery for over 1200 patients resulted in the saving of ~224 000 km of travel with likely avoided emissions in the range of 35 000–40 000 kg carbon dioxide equivalent (CO2e) over a six and half month period. Emissions arising directly from remote delivery were calculated to be <200 kg CO2e (~0.5% of those for travel), representing a significant net reduction of greenhouse gas emissions. Only one direct adverse outcome was identified, with some additional benefits identified anecdotally. Significance The use of telemedicine can make a contribution toward reduced emissions in the health care sector and, in the delivery of specialized epilepsy services, had minimal adverse clinical outcomes over the short term. However, these outcomes will likely vary with clinic locations, medical specialties and conditions.

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Abstract. Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climatecarbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable Published by Copernicus Publications on behalf of the European Geosciences Union. A. M. Foley et al.: Evaluation of biospheric components in Earth system modelsand no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process-and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.

Climate and atmospheric CO2 concentration are intimately coupled in the Earth system: CO2 influences climate through the greenhouse effect, but climate also affects CO2 through its impact on the amount of carbon stored on land and in the ocean. The change in atmospheric CO2 as a response to a change in temperature (DCO2=DT) is a useful measure to quantify the feedback between the carbon cycle and climate. Using an ensemble of experiments with an Earth system model of intermediate complexity we show a pronounced time-scale dependence of DCO2=DT. A maximum is found on centennial scales with DCO2=DT values for the model ensemble in the range 5–12 ppm C-1, while lower values are found on shorter and longer time scales. These results are consistent with estimates derived from past observations. Up to centennial scales, the land carbon response to climate dominates the CO2 signal in the atmosphere, while on longer time scales the ocean becomes important and eventually dominates on multi-millennial scales. In addition to the time-scale dependence, modeled DCO2=DT show a distinct dependence on the initial state of the system. In particular, on centennial time-scales, high DCO2=DT values are correlated with high initial land carbon content. A similar relation holds also for the CMIP5 models, although for DCO2=DT computed from a very different experimental setup. The emergence of common patterns like this could prove to usefully constrain the climate–carbon cycle feedback