Realism of rainfall in a very high-resolution regional climate model

The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection

The prevalence and nature of cardiac arrhythmias in horses following general anaesthesia and surgery

Background: The prevalence and nature of arrhythmias in horses following general anaesthesia and surgery is poorly documented. It has been proposed that horses undergoing emergency surgery for gastrointestinal disorders may be at particular risk of developing arrhythmias. Our primary objective was to determine the prevalence and nature of arrhythmias in horses following anaesthesia in a clinical setting and to establish if there was a difference in the prevalence of arrhythmias between horses with and without gastrointestinal disease undergoing surgery. Our secondary objective was to assess selected available risk factors for association with the development of arrhythmias following anaesthesia and surgery. Methods: Horses with evidence of gastrointestinal disease undergoing an exploratory laparotomy and horses with no evidence of gastrointestinal disease undergoing orthopaedic surgery between September 2009 and January 2011 were recruited prospectively. A telemetric electrocardiogram (ECG) was fitted to each horse following recovery from anaesthesia and left in place for 24 hours. Selected electrolytes were measured before, during and after surgery and data was extracted from clinical records for analysis. Recorded ECGs were analysed and the arrhythmias characterised. Multivariable logistic regression was used to identify risk factors associated with the development of arrhythmias. Results: Sixty-seven horses with gastrointestinal disease and 37 without gastrointestinal disease were recruited. Arrhythmias were very common during the post-operative period in both groups of horses. Supra-ventricular and bradyarrhythmias predominated in both groups. There were no significant differences in prevalence of any type of arrhythmias between the horses with or without gastrointestinal disease. Post-operative tachycardia and sodium derangements were associated with the development of any type of arrhythmia. Conclusions: This is the first study to report the prevalence of arrhythmias in horses during the post-operative period in a clinical setting. This study shows that arrhythmias are very common in horses following surgery. It showed no differences between those horses with or without gastrointestinal disease. Arrhythmias occurring in horses during the post-anaesthetic period require further investigation

Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization

International audienceBy coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs

UK community Earth system modelling for CMIP6

We describe the approach taken to develop the UK’s first community Earth System model, UKESM1. This is a joint effort involving the Met Office and the Natural Environment Research Council (NERC), representing the UK academic community. We document our model development procedure and the subsequent UK submission to CMIP6, based on a traceable hierarchy of coupled physical and Earth system models. UKESM1 builds on the well‐established, world‐leading HadGEM models of the physical climate system and incorporates cutting‐edge new representations of aerosols, atmospheric chemistry, terrestrial carbon and nitrogen cycles, and an advanced model of ocean biogeochemistry. A high‐level metric of overall performance shows that both the physical model, HadGEM3‐GC3.1 and UKESM1 perform better than most other CMIP6 models so far submitted for a broad range of variables. We point to much more extensive evaluation performed in other papers in this special issue. The merits of not using any forced climate change simulations within our model development process are discussed. First results from HadGEM3‐GC3.1 and UKESM1 include the emergent climate sensitivity (5.5K and 5.4K respectively) which is high relative to the current range of CMIP5 models. The role of cloud microphysics and cloud‐aerosol interactions in driving the climate sensitivity, and the systematic approach taken to understand this role is highlighted in other papers in this special issue. We place our findings within the broader modelling landscape indicating how our understanding of key processes driving higher sensitivity in the two UK models seems to align with results from a number of other CMIP6 models

Forcings, feedbacks and climate sensitivity in HadGEM3‐GC3.1 and UKESM1

Climate forcing, sensitivity and feedback metrics are evaluated in both the UK’s physical climate model HadGEM3-GC3.1at low (-LL) and medium(-MM) resolution and the UK’s Earth System Model UKESM1. The Effective Climate Sensitivity (EffCS)to a doubling of CO2 is 5.5K for HadGEM3.1-GC3.1-LL and 5.4 K for UKESM1. The transient climate response is 2.5K and 2.8K respectively. Whilst the EffCS is larger than that seen in the previous generation of models, none of the model’s forcing or feedback processes are found to be atypical of models, though the cloud feedback is at the high end. The relatively large EffCS results from an unusual combination of a typical CO2 forcing with a relatively small feedback parameter. Compared to the previous UK climate model, HadGEM3-GC2.0, the EffCS has increased from 3.2K to 5.5K due to an increase in CO2 forcing, surface albedo feedback and mid-latitude cloud feedback. All changes are well understood and due to physical improvements in the model.At higher atmospheric and ocean resolution(HadGEM3-GC3.1-MM), there is a compensation between increased marine stratocumulous cloud feedback and reduced Antarctic sea-ice feedback. In UKESM1 a CO2 fertilization effect induces a land surface vegetation change and albedo radiative effect. Historical aerosol forcing in HadGEM3-GC3.1-LL is -1.1 Wm-2. In HadGEM3-GC3.1-LL historical simulations cloud feedback is found to be less positive than in abrupt-4xCO2, in agreement with atmosphere-only experiments forced with observed historical sea-surface-temperature and sea-ice variations. However variability in the coupled model’s historical sea-ice trends hampers accurate diagnosis of the model’s total historical feedback

A pan-African convection-permitting regional climate simulation with the Met Office Unified Model: CP4-Africa

A convection-permitting multi-year regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) IMPALA (Improving Model Processes for African cLimAte) project and its configuration, domain and forcing data are described here in detail. The model (CP4-Africa) uses a 4.5km horizontal grid spacing at the equator and is run without a convection parametrization, nested within a global atmospheric model driven by observations at the sea-surface which does include a convection scheme. An additional regional simulation, with identical resolution and physical parametrizations to the global model, but with the domain, land surface and aerosol climatologies of the CP4-Africa model, has been run to aid understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parametrization and resolution. The effect of enforcing moisture conservation in the CP4-Africa model is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first 5 years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa - giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change