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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 width of the Inter-Tropical Convergence Zone (ITCZ) affects tropical rainfall, Earth's albedo, large-scale circulation, and climate sensitivity. To better understand the ITCZ width and its effects on global climate, we present a protocol to force changes in ITCZ width in climate models. Starting from an aquaplanet configuration with a slab ocean, adding surface heat fluxes in the deep tropics forces the ITCZ to narrow, and subtracting them causes it to widen. The protocol successfully generates changes in ITCZ width in all four climate models used in this study. ITCZ width in each model responds linearly to forcing magnitude and sign. Comparing across the four climate models, a response to varying ITCZ width that is remarkably consistent among models is the ITCZ strength, which is greater the narrower the ITCZ. On the other hand, the effect of varying ITCZ width on climate sensitivity is divergent among our four models, varying even in sign. Results from this pilot study highlight the connections between surface fluxes, ITCZ width, and the wider climate. A comprehensive model intercomparison project (MIP) has the potential to advance understanding of both the physical processes shaping ITCZ width and its influence on remote atmospheric circulations and global climate. [ABSTRACT FROM AUTHOR]

Tropical high cloud cover decreases with surface warming in most general circulation models. This reduction, according to the "stability‐iris" hypothesis, is thermodynamically controlled and linked to a decrease in the radiatively‐driven clear‐sky convergence, when the peak anvil clouds rise because of the rising isotherms. The influence of the large‐scale dynamical changes on the tropical high cloud fraction remains difficult to disentangle from the local thermodynamic influence, given that the mean meridional circulation remains inextricably tied to the local thermodynamic structure of the atmosphere. However, using idealized general circulation model simulations, we propose a novel method to segregate the dynamical impact from the thermodynamic impact on the tropical high cloud fraction. To this end, our investigation primarily focuses on the mechanisms underpinning changes in the high cloud cover in the deep tropics in response to extratropical surface warming, when the tropical sea surface temperatures remain invariant. Net convective detrainment of ice cloud condensates decreases at the peak detrainment region, without a rise in its altitude. We also find that the importance of depositional growth of ice cloud condensates in controlling the high cloud fraction response in the deep tropics varies with altitude. Plain Language Summary: The cloud feedback associated with changes in the tropical high cloud cover is one of the major uncertainties in calculating the current estimates of climate sensitivity, which is a measure of how much the Earth's average surface temperature would increase if we double the amount of atmospheric carbon dioxide. When the surface becomes warmer in the tropics, the tropical high cloud cover decreases. However, this raises an important question: how do circulation changes independent of the temperature changes within the tropics impact the tropical high cloud cover? Using idealized general circulation model simulations, we found that the tropical high cloud fraction decreases as a result of circulation changes induced by extratropical warming, even when the tropical sea surface temperatures are held constant. Both convective and cloud microphysical processes play significant roles in controlling the changes in tropical high cloud fraction, and their relative importance varies with altitude. Understanding the different factors responsible for the changes in high cloud cover is important, as the area covered by these tropical high clouds can affect how much the Earth warms under climate change. Key Points: An indirect weakening of the Hadley circulation decreases the convectively‐detrained ice cloud condensates in the deep tropicsA concurrent reduction in the net vertical transport of water vapor limits the depositional growth of ice cloud condensatesThe relative influence of depositional growth to net convective detrainment on the tropical high cloud response is altitude‐dependent [ABSTRACT FROM AUTHOR]

The eventual planetary warming in response to elevated atmospheric carbon dioxide concentrations is not precisely known. This climate sensitivity S depends primarily on the net physical climate feedbacks, usually denoted as λ. Multiple lines of evidence can constrain this feedback parameter: proxy-based and model evidence from past equilibrium climates, process-based understanding of the physics underlying changes, and recent observations of temperature change, top-of-atmosphere energy imbalance, and ocean heat content. However, despite recent advances in combining these lines of evidence, the estimated range of S remains large. Here, using a Bayesian framework, we discuss three sources of uncertainty: uncertainty in the evidence, structural uncertainty in the model used to interpret that evidence, and differing prior beliefs, and show how these affect the conclusions we may draw from a single line of evidence. We then propose a method to combine multiple estimates of the evidence, multiple multiple explanatory models, and the subjective assessments of different experts in order to arrive at an assessment of λ (and hence, climate sensitivity S) that may be rapidly updated as new information arrives and truly reflects the existing community of experts. [ABSTRACT FROM AUTHOR]

We investigate positive subtropical low cloud feedback mechanisms in climate models which have performed the CMIP6/CFMIP‐3 AMIP and AMIP uniform +4K experiments while saving CFMIP‐3 process diagnostics on model levels. Our analysis focuses on the trade cumulus/stratocumulus transition region between California and Hawaii, where positive low cloud feedbacks are present in the JJA season. We introduce a methodology to test various positive cloud feedback mechanisms proposed in the literature as the main causes of the low cloud responses in the models. Causal hypotheses are tested by comparing their predictions with the models' responses of clouds, cloud controlling factors, boundary layer depth and temperature/humidity tendencies to climate warming. Changes in boundary layer depth, relative humidity in the cloud layer, convective moistening rate and large‐scale humidity advection at the top of the boundary layer are shown to be crucial for identifying the main causes of the low cloud reductions in the models. For the cases examined, our approach narrows down the seven mechanisms considered to between one and three remaining candidates for each model. No single mechanism considered can explain the feedback in all of the models at the locations examined, but the surface latent heat flux/convective entrainment mechanism remains a candidate for BCC‐CSM2‐MR, IPSL‐CM6A‐LR, and MRI‐ESM2.0, while the surface upwelling longwave mechanism remains for CESM2, HadGEM3‐GC3.1‐LL, and MIROC6. Plain Language Summary: Climate models show reductions in low‐level clouds with the warming climate which are poorly understood. We examine cloud changes between California and Hawaii in six climate models. We consider seven potential explanations for the changes. We find that examining changes in the height of low level clouds, the moistening of the atmosphere by rising plumes of moist air, the humidity of the air and the rate at which dry air is mixed into the clouds from above allows us to narrow down the number of explanations compatible with each model. Key Points: Hypotheses for positive cumulus/stratocumulus feedback mechanisms are tested in six climate modelsWe narrow down the seven mechanisms considered to between one and three candidates for each modelBoundary layer depth, relative humidity, convective moistening, and humidity advection are key [ABSTRACT FROM AUTHOR]

The acute locked knee is an orthopaedic emergency requiring prompt diagnosis and treatment. It can be classified as acute or chronic. The term 'locked knee' refers to a knee that demonstrates fixed flexion or which has a 'block' to complete extension. Some degree of active or passive extension may be achievable, but not full extension. The most frequent causes of a locked knee are a meniscal tear, rupture of the anterior cruciate ligament or loose bodies. Magnetic resonance imaging is the gold standard in diagnostic imaging. Knee arthroscopy is considered the gold standard in management. This article gives an overview of the presentation, assessment and management of the locked knee for core surgical, acute care common stem and emergency medicine trainees. [ABSTRACT FROM AUTHOR]

We compare the radiative feedbacks in an ensemble of global climate models under uniform 4 K warming and cooling of sea surface temperatures. The global‐mean net feedback is less stabilizing under warming in all nine models. This results primarily from less stabilizing water vapor and extra‐tropical shortwave cloud feedbacks, partially offset by more stabilizing tropical cloud feedbacks. The zonal‐mean feedbacks are also robust across the ensemble. In the extra‐tropics, the less stabilizing shortwave cloud feedback under warming is associated with further poleward migration of the mean Southern Hemisphere jet in some models. However, additional experiments with an aquaplanet version of the HadGEM3 model suggest that the asymmetry of the jet shift is not driving the asymmetry in the cloud feedbacks at these latitudes. In the tropics, the stronger water vapor feedback under warming is offset by weaker shortwave cloud feedbacks. The result is that the ensemble spread in the differences between the global feedbacks under warming and cooling is mainly driven by their differences in the tropics. The spatial distribution of the feedbacks largely reflects the zonal‐mean behavior, although there is considerable model spread in the regional cloud feedbacks, particularly in the tropical shortwave cloud feedback. Comparison with CO2‐ and solar‐forced coupled experiments suggests that the global‐mean longwave cloud feedback is nearly invariant to warming and cooling, regardless of the nature of the forcing. The shortwave cloud feedback is generally more positive under warming in the coupled models, consistent with the uniform SST perturbation experiments. Plain Language Summary: A longstanding question in climate science is whether the study of cooler past climates can help us to understand future climate change in response to increasing CO2 and other greenhouse gases. Answering this question is difficult because when the Earth was much colder the climate itself was quite different from today's. This means that we cannot be sure that feedbacks in the climate system operated as they do now, or as they might do in the future. To simplify the problem we have examined climate model experiments in which the surface temperature of the oceans is alternately warmed and cooled by a fixed amount relative to the present day. This provides us with a baseline for understanding the differences between more realistic scenarios of past and future climates. We highlight the role of clouds and atmospheric water vapor in determing these differences and the relative importance of the tropics compared to higher latitudes. Key Points: The global climate feedback is robustly less stabilizing under warming compared to coolingThis is driven by water vapor and extra‐tropical shortwave cloud feedbacks, partially offset by more stabilizing tropical cloud feedbacksSimplified climate model experiments are a valuable tool to help us understand climate feedbacks in colder and warmer climates [ABSTRACT FROM AUTHOR]