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A variety of evidence shows that social categorization of people based on their race can lead to stereotypical judgements and prejudicial behaviour. Here, we explore the extent to which trait judgements of faces are influenced by race. To address this issue, we measured the reliability of first impressions for own-race and other-race faces in Asian and White participants. Participants viewed pairs of faces and were asked to indicate which of the two faces was more dominant or which of the two faces was more trustworthy. We measured the consistency (or reliability) of these judgements across participants for own-race and other-races faces. We found that judgements of dominance or trustworthiness showed similar levels of reliability for own-race and other-race faces. Moreover, an item analysis showed that the judgements on individual trials were very similar across participants from different races. Next, participants made overall ratings of dominance and trustworthiness from own-race and other-race faces. Again, we found that there was no evidence for an ORE. Together, these results provide a new approach to measuring trait judgements of faces and show that in these conditions there is no ORE for the perception of dominance and trustworthiness. [ABSTRACT FROM AUTHOR]

Climate feedbacks over the historical period (here defined as 1850–2014) have been investigated in large ensembles of historical and single forcing experiments (hist‐ghg, hist‐aer, and hist‐nat), with 47 members for each experiment. Across the historical ensemble with all forcings, a range in estimated Effective Climate Sensitivity (EffCS) between approximately 3–6 K is found, a considerable spread stemming solely from initial condition uncertainty. The spread in EffCS is associated with varying Sea Surface Temperature (SST) patterns seen across the ensemble due to their influence on different feedback processes. For example, the level of polar amplification is strongly correlated with the amount of sea ice melt per degree of global warming. This mechanism is related to the large spread in shortwave clear‐sky feedbacks and is the main contributor to the different forcing efficacies seen across the different forcing agents, although in HadGEM3‐GC3.1‐LL these differences in forcing efficacy are shown to be small. The spread in other feedbacks is also investigated, with the level of tropical SST warming strongly correlated with the longwave clear‐sky feedbacks, and the local surface‐air‐temperatures well correlated with the spread in cloud radiative effect feedbacks. The metrics used to understand the spread in feedbacks can also help to explain the disparity between feedbacks seen in the historical experiment simulations and modeled estimate of the feedbacks seen in the real world derived from an atmosphere‐only experiment prescribed with observed SSTs (termed amip‐piForcing). Plain Language Summary: Understanding how the Earth's climate responds to an imposed forcing such as an increase in greenhouse gases or aerosols is an important issue relevant to climate mitigation and adaptation policies on the global scale. One way we can understand this is by analysing the historical period (1850–2014), a period over which the climate has already changed substantially due to human induced forcings, and also a period over which observations allow us to compare modeled changes in climate with the changes seen in the real world. Here, we use a large ensemble of climate model simulations of the historical period where we aim to understand (a) how natural variability causes differences in the global temperature response to the same imposed forcing, (b) what causes different forcing agents (e.g., greenhouse gases or aerosols) to be more or less effective at warming or cooling the planet, and (c) whether historical simulations—where the climate model simulates its own sea surface temperatures—capture the same response to historical forcings as an atmosphere‐only simulation prescribed with observed sea surface temperatures. We find that the pattern of sea surface temperatures (particularly the levels of tropical and polar warming) is key to understanding each of these points. Key Points: Natural variability causes a 3–6 K range in Effective Climate Sensitivity in a large single model ensemble of historical simulationsTropical and polar warming are strongly related to the spread in longwave clear‐sky and shortwave clear‐sky feedbacks respectivelyDeficiencies in simulating observed tropical and polar warming cause different feedbacks in historical and amip‐piForcing experiments [ABSTRACT FROM AUTHOR]

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 describedThe climate model's global temperature response to different anthropogenic and natural drivers is examined and compared to other modelsSouthern Ocean temperature variability is unusual and sensitive to climate driver [ABSTRACT FROM AUTHOR]

Aim: A treatment strategy for patients with a significant polyp or early colon cancer (SPECC) of the rectum presents a challenge due to the significant rate of covert malignancy and lack of standardized assessment. For this reason, NICE recommends multidisciplinary meetings to improve outcomes. The primary aim of the present study was to report the performance of our specialist early rectal cancer (SERC) multidisciplinary team (MDT) in correctly substratifying the risk of cancer and to discuss the limitations of staging investigations in those patients with "poor outcomes". Method: This was a retrospective review of patients referred to our SERC MDT from 2014 to 2019. Lesions were assigned by the MDT to three pre‐resection categories (low, intermediate, high) according to the risk of covert malignancy. Resection method and final histology were compared to the pre‐resection categories. Results: Of 350 SPECC lesions, 174 were assessed as low‐risk, 108 intermediate‐risk and 68 high‐risk. The cancer incidence was 4.8%, 8.3% and 53%, respectively (15.5% overall). Eight lesions were categorized as low‐risk but following piecemeal resection were found to be malignant. Five lesions, three of which were categorized as high‐risk, were ultimately benign following conventional surgery. One pT1sm1 cancer, removed by anterior resection, may have been treated by local excision. Conclusion: A total of 83% of malignant polyps were triaged to an en bloc resection technique and surgical resection avoided for nearly all benign lesions. However, 12 patients from this cohort were deemed to have a poor outcome because of miscategorization. Further comparative research is needed to establish the optimum strategy for rectal SPECC lesion assessment. Originality statement: There is currently no consensus for staging significant polyps of the rectum. This paper reports the effectiveness of a specialist early rectal cancer MDT to correctly risk‐stratify significant rectal polyps. It underscores the importance of accurate categorization for treatment decision‐making, while acknowledging the limitations of current staging modalities. [ABSTRACT FROM AUTHOR]

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)--key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections. [ABSTRACT FROM AUTHOR]