Explore the vast range of titles available.

The Brewer–Dobson circulation (BDC) is a key feature of the stratosphere that models need to accurately represent in order to simulate surface climate variability and change adequately. For the first time, the Climate Model Intercomparison Project includes in its phase 6 (CMIP6) a set of diagnostics that allow for careful evaluation of the BDC. Here, the BDC is evaluated against observations and reanalyses using historical simulations. CMIP6 results confirm the well-known inconsistency in the sign of BDC trends between observations and models in the middle and upper stratosphere. Nevertheless, the large uncertainty in the observational trend estimates opens the door to compatibility. In particular, when accounting for the limited sampling of the observations, model and observational trend error bars overlap in 40 % of the simulations with available output. The increasing CO2 simulations feature an acceleration of the BDC but reveal a large spread in the middle-to-upper stratospheric trends, possibly related to the parameterized gravity wave forcing. The very close connection between the shallow branch of the residual circulation and surface temperature is highlighted, which is absent in the deep branch. The trends in mean age of air are shown to be more robust throughout the stratosphere than those in the residual circulation.

Tropical stratospheric variability is investigated in ensembles of historical simulations performed by nine models for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Realizations from all the models feature a reasonable quasi‐biennial oscillation (QBO). Variability in the zonal mean zonal winds at the equator is found to be coherent among realizations when a model prescribes the CMIP6 ozone forcing. No such coherence is found when a model simulates ozone. The coherence results in an ensemble mean QBO signal with amplitude, depending on the model, 50%–80% of the mean QBO amplitude from a single realization from the same model. The ensemble mean signal is due to synchronization of QBO phases, attributed to the CMIP6 protocol including a QBO signal in the ozone forcing. Coherence in models using the CMIP6 ozone is, therefore, artificial and individual realizations from these models are not completely independent. Plain Language Summary High above the equator winds in the stratosphere at altitudes from ∼16–40 km repeatedly switch direction from eastward to westward, and back again, roughly every 14 months. This so‐called quasi‐biennial oscillation (QBO) featured in only a subset of the simulations of the historical period that provided input for the latest international assessments of climate change. Variability in the stratospheric winds at the equator in these simulations is found to be remarkably coherent across ensembles of realizations from the individual models, but only for those models that did not simulate ozone variability. Instead, these models followed a common protocol that specified prescribing an ozone distribution that included a QBO in the tropical stratosphere. For each of the models this causes the simulated QBOs in the winds to synchronize across many realizations of the historical period. Consequently variability in the equatorial stratosphere in these realizations becomes coherent. However, this coherence is not real as it is merely an artifact of the simulations following the agreed ozone protocol. Likewise, due to the design of the protocol, individual realizations from these models can not be considered as been entirely independent in the tropical stratosphere. Key Points Coupled Model Intercomparison Project phase 6 (CMIP6) historical simulations from several models feature a realistic quasi‐biennial oscillation (QBO) in the equatorial stratosphere QBO phases synchronize across ensembles of realizations from models not able to simulate evolving ozone The phase synchronization is artificial and attributed to the CMIP6 protocol prescribing a QBO signal in the ozone forcing data

We describe and evaluate historical simulations which use the third Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 (HadGEM3‐GC3.1) model and which form part of the UK's contribution to the sixth Coupled Model Intercomparison Project, CMIP6. These simulations, run at two resolutions, respond to historically evolving forcings such as greenhouse gases, aerosols, solar irradiance, volcanic aerosols, land use, and ozone concentrations. We assess the response of the simulations to these historical forcings and compare against the observational record. This includes the evolution of global mean surface temperature, ocean heat content, sea ice extent, ice sheet mass balance, permafrost extent, snow cover, North Atlantic sea surface temperature and circulation, and decadal precipitation. We find that the simulated time evolution of global mean surface temperature broadly follows the observed record but with important quantitative differences which we find are most likely attributable to strong effective radiative forcing from anthropogenic aerosols and a weak pattern of sea surface temperature response in the low to middle latitudes to volcanic eruptions. We also find evidence that anthropogenic aerosol forcings play a role in driving the Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation, which are key features of the North Atlantic ocean. Overall, the model historical simulations show many features in common with the observed record over the period 1850–2014 and so provide a basis for future in‐depth study of recent climate change. Plain Language Summary Historical simulations, which successfully reproduce features of the observed climate from the end of the preindustrial period to the near‐present day, contribute to our understanding of the underlying mechanisms that drive or influence climate variability and climate change. The historical simulations described in this paper use the third Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 model. These simulations form part of the UK's contribution to the sixth Coupled Model Intercomparison Project. We assess various aspects of the historical climate system in our simulations against observations. This includes the evolution of global mean surface temperature, ocean heat content, sea ice extent, ice sheet mass balance, permafrost extent, snow cover, North Atlantic sea surface temperature and circulation, and decadal precipitation. The key findings include (a) that the model global mean surface temperature broadly follows the observed record, with a few quantitative differences, and (b) that the ocean circulation and sea surface temperatures of the North Atlantic are likely influenced by historical forcings. In general, the simulations respond to historically evolving influences in a similar manner to the observed world. Therefore, these simulations contribute, as part of the wider CMIP6 multimodel effort, to the understanding of the causes of observed climate change since 1850. Key Points We describe and evaluate the UK's CMIP6 historical simulations We identify drivers of the modeled global temperature evolution and compare with the observed record We find that anthropogenic aerosol forcings influence the simulation of North Atlantic ocean variability

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

The North Atlantic Oscillation (NAO), the regional manifestation of the Arctic Oscillation (AO), dominates winter climate variability in Europe and North America. Skilful seasonal forecasting of the winter NAO/AO has been demonstrated recently by dynamical prediction systems. However, the role of initial conditions in this predictability remains unknown. Using a latest generation seasonal forecasting system and reanalysis data, we show that the initial upper stratospheric zonal wind anomaly contributes to winter NAO/AO predictability through downward propagation of initial conditions. An initial polar westerly/easterly anomaly in the upper stratosphere propagates down to the troposphere in early winter, favoring a poleward/equatorward shift of the tropospheric mid-latitude jet. This tropospheric anomaly persists well into the late winter and induces the positive/negative phase of NAO/AO in the troposphere. Our results imply that good representation of stratospheric initial condition and stratosphere-troposphere coupling in models is important for winter climate prediction.

The UK contribution to the Detection and Attribution Model Intercomparison Project (DAMIP), part of the sixth phase of the Climate Model Intercomparison Project (CMIP6), is described. The lower atmosphere and ocean resolution configuration of the latest Hadley Centre global environmental model, HadGEM3‐GC3.1, is used to create simulations driven either with historical changes in anthropogenic well‐mixed greenhouse gases, anthropogenic aerosols, or natural climate factors. Global mean near‐surface air temperatures from the HadGEM3‐GC31‐LL simulations are consistent with CMIP6 model ensembles for the equivalent experiments. While the HadGEM3‐GC31‐LL simulations with anthropogenic and natural forcing factors capture the overall observed warming, the lack of marked simulated warming until the 1990s is diagnosed as due to aerosol cooling mostly offsetting the well‐mixed greenhouse gas warming until then. The model has unusual temperature variability over the Southern Ocean related to occasional deep convection bringing heat to the surface. This is most prominent in the model's aerosol only simulations, which have the curious feature of warming in the high southern latitudes, while the rest of the globe cools, a behavior not seen in other CMIP6 models. This has implications for studies that assume model responses, from different climate drivers, can be linearly combined. While DAMIP was predominantly designed for detection and attribution studies, the experiments are also very valuable for understanding how different climate drivers influence a model, and thus for interpretating the responses of combined anthropogenic and natural driven simulations. We recommend institutions provide model simulations for the high priority DAMIP experiments. Plain Language Summary We describe the UK submission to the Detection and Attribution Model Intercomparison Project (DAMIP), using the HadGEM3‐GC3.1 climate model. The model's near‐surface temperature responses to different human and natural climate drivers are compared with other climate models and observed temperature changes. The experiments help to understand the evolution of the model's simulated historical global temperatures. One of the more interesting model features is the variability in the Southern Ocean which manifests itself as occasional surface warming due to deep ocean heat coming to the surface. This behavior, which occurs more often in simulations that cool than in simulations that warm, appears to be unusual compared to other models. The investigation of this model behavior demonstrates that DAMIP model experiments are not just useful for climate change detection and attribution, but also for understanding how a model responds to different climate drivers. Climate model participation in DAMIP is encouraged. Key Points The UK's contribution to the Detection and Attribution Model Intercomparison project (DAMIP) is described The climate model's global temperature response to different anthropogenic and natural drivers is examined and compared to other models Southern Ocean temperature variability is unusual and sensitive to climate driver

Using a large ensemble of initialised retrospective forecasts (hindcasts) from a seasonal prediction system, we explore various statistics relating to sudden stratospheric warmings (SSWs). Observations show that SSWs occur at a similar frequency during both El Niño and La Niña northern hemisphere winters. This is contrary to expectation, as the stronger stratospheric polar vortex associated with La Niña years might be expected to result in fewer of these extreme breakdowns. Here we show that this similar frequency may have occurred by chance due to the limited sample of years in the observational record. We also show that in these hindcasts, winters with two SSWs, a rare event in the observational record, on average have an increased surface impact. Multiple SSW events occur at a lower rate than expected if events were independent but somewhat surprisingly, our analysis also indicates a risk, albeit small, of winters with three or more SSWs, as yet an unseen event. Observed SSWs occur at a similar frequency during both El Niño and La Niña. This is contrary to expectation, as the stronger stratospheric polar vortex associated with La Niña might be expected to result in fewer of these extreme breakdowns. Using a large ensemble of initialised hindcasts from a seasonal prediction system, we show that this similar frequency may have occurred by chance due to the limited sample of years in the observational record. We also examine the impacts and likelihood of multiple SSW events.

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

We document the development of the first version of the U.K. Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre‐industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC−1. Plain Language Summary We describe the development and behavior of UKESM1, a novel climate model that includes improved representations of processes in the atmosphere, ocean, and on land. These processes are inter‐related: For example, dust is produced on the land and blown up into the atmosphere where it affects the amount of sunlight falling on Earth. Dust can also be dissolved in the ocean, where it affects marine life. This in turn changes both the amount of carbon dioxide absorbed by the ocean and the material emitted from the surface into the atmosphere, which has an affect on the formation of clouds. UKESM1 includes many processes and interactions such as these, giving it a high level of complexity. Ensuring realistic process behavior is a major challenge in the development of our model, and we have carefully tested this. UKESM1 performs well, correctly exhibiting stable results from a continuous pre‐industrial simulation (used to provide a reference for future experiments) and showing good agreement with observations toward the end of its historical simulations. Results for some properties—including the degree to which average surface temperature changes with increased amounts of carbon dioxide in the atmosphere—are examined in detail. Key Points UKESM1 represents a major advance over its predecessor HadGEM2‐ES, both in the complexity of its components and its internal coupling The complex coupling presents challenges to the model development; we document the tuning process employed to obtain acceptable performance UKESM1 performs well, having a stable pre‐industrial state and showing good agreement with observations in a wide variety of contexts

A necessary step before assessing the performance of decadal predictions is the evaluation of the processes that bring memory to the climate system, both in climate models and observations. These mechanisms are particularly relevant in the North Atlantic, where the ocean circulation, related to both the Subpolar Gyre and the Meridional Overturning Circulation (AMOC), is thought to be important for driving significant heat content anomalies. Recently, a rapid decline in observed densities in the deep Labrador Sea has pointed to an ongoing slowdown of the AMOC strength taking place since the mid 90s, a decline also hinted by in-situ observations from the RAPID array. This study explores the use of Labrador Sea densities as a precursor of the ocean circulation changes, by analysing a 300-year long simulation with the state-of-the-art coupled model HadGEM3-GC2. The major drivers of Labrador Sea density variability are investigated, and are characterised by three major contributions. First, the integrated effect of local surface heat fluxes, mainly driven by year-to-year changes in the North Atlantic Oscillation, which accounts for 62% of the total variance. Additionally, two multidecadal-to-centennial contributions from the Greenland–Scotland Ridge outflows are quantified; the first associated with freshwater exports via the East Greenland Current, and the second with density changes in the Denmark Strait Overflow. Finally, evidence is shown that decadal trends in Labrador Sea densities are followed by important atmospheric impacts. In particular, a positive winter NAO response appears to follow the negative Labrador Sea density trends, and provides a phase reversal mechanism.