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African society is particularly vulnerable to climate change. The representation of convection in climate models has so far restricted our ability to accurately simulate African weather extremes, limiting climate change predictions. Here we show results from climate change experiments with a convection-permitting (4.5 km grid-spacing) model, for the first time over an Africa-wide domain (CP4A). The model realistically captures hourly rainfall characteristics, unlike coarser resolution models. CP4A shows greater future increases in extreme 3-hourly precipitation compared to a convection-parameterised 25 km model (R25). CP4A also shows future increases in dry spell length during the wet season over western and central Africa, weaker or not apparent in R25. These differences relate to the more realistic representation of convection in CP4A, and its response to increasing atmospheric moisture and stability. We conclude that, with the more accurate representation of convection, projected changes in both wet and dry extremes over Africa may be more severe. For the first time, climate change experiments with a convection-permitting model have been carried out over an Africa-wide domain. These show more severe future changes in both wet and dry extremes over Africa compared to a traditional coarser resolution 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.

Climate forcing, sensitivity, and feedback metrics are evaluated in both the United Kingdom's physical climate model HadGEM3‐GC3.1 at low (‐LL) and medium (‐MM) resolution and the United Kingdom's Earth System Model UKESM1. The effective climate sensitivity (EffCS) to a doubling of CO2 is 5.5 K for HadGEM3.1‐GC3.1‐LL and 5.4 K for UKESM1. The transient climate response is 2.5 and 2.8 K, respectively. While 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 U.K. climate model, HadGEM3‐GC2.0, the EffCS has increased from 3.2 to 5.5 K due to an increase in CO2 forcing, surface albedo feedback, and midlatitude 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 stratocumulus 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 W m−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. Plain Language Summary A new generation of climate models—called HadGEM3‐GC3.1 and UKESM1—have been developed in the United Kingdom and will be used widely in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Evaluating the models' benchmark climate sensitivity and feedback metrics is a useful first step to understanding their characteristic response to forcing. The effective climate sensitivities are found to be higher than that seen in the previous generation of models, in common with other recently developed climate models. Reasons for this are discussed. Key Points HadGEM3‐GC3.1 and UKESM1 have climate sensitivities of 5.5 and 5.4 K, respectively Our models' forcing and feedback processes are not atypical of models in general The relatively large climate sensitivity arises from an unusual combination of forcing and feedback

In atmospheric models with kilometer‐scale grids the resolution approaches the scale of convection. As a consequence the most energetic eddies in the atmosphere are partially resolved and partially unresolved. The modeling challenge to represent convection partially explicitly and partially as a subgrid process is called the convective gray zone problem. The gray zone issue has previously been discussed in the context of regional models, but the evolution in regional models is constrained by the lateral boundary conditions. Here we explore the convective gray zone starting from a defined global configuration of the Met Office Unified Model using initialized forecasts and comparing different model formulations to observations. The focus is on convection and turbulence, but some aspects of the model dynamics are also considered. The global model is run at nominal 5 km resolution and thus contributions from both resolved and subgrid turbulent and convective fluxes are non‐negligible. The main conclusion is that in the present assessment, the configurations which include scale‐aware turbulence and a carefully reduced and simplified mass‐flux convection scheme outperform both the configuration with fully parameterized convection as well as a configuration in which the subgrid convection parameterization is switched off completely. The results are more conclusive with regard to convective organization and tropical variability than extratropical predictability. The present study thus endorses the strategy to further develop scale‐aware physics schemes and to pursue an operational implementation of the global 5 km‐resolution model to be used alongside other ensemble forecasts to allow researchers and forecasters to further assess these simulations. Plain Language Summary An in‐depth exploration of kilometer‐scale global atmospheric modeling in the context of the current Met Office modeling system, the Met Office Unified Model, is presented. All simulations were performed using a global atmosphere model at nominal 5 km resolution. The model resolution thus resides in the so‐called convective gray zone where the grid length approaches the scale of turbulence and convection, and contributions from both resolved and subgrid convective and turbulent fluxes are non‐negligible. A case study approach has been taken in which various testbed cases are defined and model forecasts are evaluated against observations. The focus is on the representation of convection, turbulence and dynamics, the key aspects of the model formulation in the convective gray zone. The main finding is that in the present assessment the configurations which include a scale‐aware representation of turbulence and a carefully reduced and simplified convection scheme outperform both the reference model with fully parameterized convection as well as a configuration in which the subgrid convection parameterization is switched off completely. An outlook on further work toward the development of an adequate kilometer‐scale resolution global coupled modeling system for use across weather and climate time scales is given. Key Points The representation of turbulence and convection in the convective gray zone is investigated at global 5 km resolution In the examined context a reduced mass‐flux convection scheme is beneficial in 5 km‐resolution global model forecasts The assessment is more conclusive with regard to convective organization and tropical variability than extratropical predictability

We describe the approach taken to develop the United Kingdom'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 U.K. academic community. We document our model development procedure and the subsequent U.K. 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 models, 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 (5.5 and 5.4 K, 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 modeling landscape indicating how our understanding of key processes driving higher sensitivity in the two U.K. models seems to align with results from a number of other CMIP6 models. Plain Language Summary The United Kingdom has taken a community approach to model development and delivery of simulations to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The papers in this special issue characterize and evaluate the U.K. models and highlight emerging properties of the models, such as the climate sensitivity. Understanding of the reasons for an increase in sensitivity in these new models is highlighted here, and similarities to our findings from other modeling centers are discussed. Key Points The United Kingdom has developed its first community Earth system model and delivered a traceable hierarchy of models to CMIP6 We applied a process‐based evaluation strategy in model development but chose not to use historic trends or measures of climate response The U.K. models exhibit higher climate sensitivity than seen in CMIP5 arising in part from more positive cloud feedbacks

By 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.

Changes in precipitation extremes are occurring under climate change, but how they will manifest on sub-daily timescales is uncertain. This study used a high-resolution model, typically used for weather forecasting, to simulate hourly rainfall in the UK in the year 2100. The results confirmed previous findings of winter rainfall intensification and found that short-duration rainfall intensified in summer, increasing the risk of flash flooding. The intensification of precipitation extremes with climate change 1 is of key importance to society as a result of the large impact through flooding. Observations show that heavy rainfall is increasing on daily timescales in many regions 2 , but how changes will manifest themselves on sub-daily timescales remains highly uncertain. Here we perform the first climate change experiments with a very high resolution (1.5 km grid spacing) model more typically used for weather forecasting, in this instance for a region of the UK. The model simulates realistic hourly rainfall characteristics, including extremes 3 , 4 , unlike coarser resolution climate models 5 , 6 , giving us confidence in its ability to project future changes at this timescale. We find the 1.5 km model shows increases in hourly rainfall intensities in winter, consistent with projections from a coarser 12 km resolution model and previous studies at the daily timescale 7 . However, the 1.5 km model also shows a future intensification of short-duration rain in summer, with significantly more events exceeding the high thresholds indicative of serious flash flooding. We conclude that accurate representation of the local storm dynamics is an essential requirement for predicting changes to convective extremes; when included we find for the model here that summer downpours intensify with warming.

The Coupled Model Intercomparison Project 6 protocol suggests prescribing preindustrial ozone concentrations in abrupt‐4xCO2 simulations. This leads to a mismatch between the thermal tropopause, which rises due to climate change, and the ozone tropopause, which remains fixed. The result is unphysically high ozone concentrations in the upper troposphere, leading to a warm bias in cold point temperature and increased stratospheric water vapor. In the U.K. physical climate model HadGEM3‐GC3.1 this increases the surface climate sensitivity. In the future, other climate models without interactive ozone schemes may face similar problems. We describe a method to interactively redistribute ozone in climate simulations, which removes the inconsistency between the thermal and ozone tropopause heights while retaining the prescribed ozone distribution as closely as possible. This removes unphysical consequences of the tropopause mismatch, while still allowing a fair comparison against other Coupled Model Intercomparison Project 6 model simulations. After each model year, the monthly mean, zonal mean, thermal tropopause is formed based on the previous two model years. The ozone tropopause is defined at 1 km below the thermal tropopause by setting ozone concentrations there to 80 ppbv, and smoothing appropriately. The mass of ozone removed from the troposphere is added to the stratosphere thus conserving the total mass of ozone. This redistribution is then applied proportionally to the 3‐D monthly mean ozone concentrations. The climate model is run for the following year, using this redistributed ozone, and then the whole process is repeated. Results are presented from preindustrial and abrupt‐4xCO2 simulations, but this method can be used for any climate simulation. Key Points Prescribed ozone in climate projections leads to unphysical ozone amounts in the upper troposphere These impact stratospheric water vapor and surface temperature Simple ozone redistribution is able to remove these impacts

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.

A convection-permitting multiyear 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) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM(CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, 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 parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five 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.