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Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate model emulators have a crucial role in assessing warming levels of many emission scenarios from probabilistic climate projections based on new insights into Earth system response to CO2 and other forcing factors. This article describes one such tool, MCE, from model formulation to application examples associated with a recent model intercomparison study. The MCE is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters for probabilistic projections are generated from statistical models and constrained with a Metropolis–Hastings independence sampler. Some of the model parameters associated with CO2-induced warming have a covariance structure, as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). Perturbed ensembles can cover the diversity of CMIP models effectively, and they can be constrained to agree with several climate indicators such as historical warming. The model's simplicity and resulting successful calibration imply that a method with less complicated structures and fewer control parameters offers advantages when building reasonable perturbed ensembles in a transparent way. Experimental results for future scenarios show distinct differences between CMIP-consistent and observation-consistent ensembles, suggesting that perturbed ensembles for scenario assessment need to be properly constrained with new insights into forced response over historical periods.

Long-term climate experiments up to the year 2300 have been conducted using two full-scale complex Earth system models (ESMs), CESM1(BGC) and MIROC-ESM, for a CO2 emissions reduction pathway, termed Z650, where annual CO2 emissions peak at 11 PgC in 2020, decline by 50% every 30 years, and reach zero in 2160. The results have been examined by focusing on the approximate linear relationship between the temperature increase and cumulative CO2 emissions. Although the temperature increase is nearly proportional to the cumulative CO2 emissions in both models, this relationship does not necessarily provide a robust basis for the restriction of CO2 emissions because it is substantially modulated by non-CO2 forcing. CO2-induced warming, estimated from the atmospheric CO2 concentrations in the models, indicates an approximate compensation of nonlinear changes between fast-mode responses to concentration changes at less than 10 years and slow-mode response at more than 100 years due to the thermal inertia of the ocean. In this estimate, CESM1(BGC) closely approximates a linear trend of 1.7 °C per 1000 PgC, whereas MIROC-ESM shows a deviation toward higher temperatures after the emissions peak, from 1.8 °C to 2.4 °C per 1000 PgC over the range of 400-850 PgC cumulative emissions corresponding to years 2000-2050. The evolution of temperature under zero emissions, 2160-2300, shows a slight decrease of about 0.1 °C per century in CESM1(BGC), but remains almost constant in MIROC-ESM. The fast-mode response toward the equilibrium state decreases with a decrease in the airborne fraction owing to continued CO2 uptake (carbon cycle inertia), whereas the slow-mode response results in more warming owing to continued heat uptake (thermal inertia). Several specific differences are noted between the two models regarding the degree of this compensation and in some key regional aspects associated with sustained warming and long-term climate risks. Overall, elevated temperatures continue for at least a few hundred years under zero emissions.

Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis, and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard impulse response model used for greenhouse gas (GHG) metric calculations in the IPCC's Fifth Assessment Report, plus one additional physically motivated equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth system models and observations. These six equations are transparent and sufficiently simple that the model is able to be ported into standard tabular data analysis packages, such as Excel, increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a million-member ensemble, using the constrained ensemble to make scenario-dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased “hot” or “cold”: it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications and therefore could be used as a lowest-common-denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts.

A long‐term numerical experiment has been conducted using the Whole Atmosphere Community Climate Model (WACCM) to investigate the response of the middle atmosphere to time‐varying spectral solar irradiance over multiple 11‐year cycles, modeled on the basis of observed 10.7‐cm radio flux (F10.7). The model domain covers from the Earth's surface to the lower thermosphere with approximately two‐degree horizontal resolution and 66 vertical layers. Sea surface temperatures are prescribed by a climatological annual cycle, and boundary data for chemical compositions are held constant. The experiment does not include spontaneous nor imposed quasi‐biennial oscillation. Temperature and ozone differences near the stratopause between solar max and min, typically 0.8 K and 1.6% corresponding to approximately 100 units of F10.7 variation, have general agreement with the current scientific understanding. The model's dynamical responses as an indirect solar effect are substantially weak during winter against evidences from past empirical studies. The indirect solar signal tends to appear when the polar vortex becomes weak. The most striking signal is more frequent stratospheric sudden warmings during solar max in the Northern Hemisphere late winter through early spring, supporting observed tendencies. This modulation has an aspect of the annular mode and results in a major impact on the troposphere in early spring. Such a signal, however, does not appear in the Southern Hemisphere where the model has a westerly bias. There is no marked response in the equatorial lower stratosphere.

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Midkine (MK) is a product of a retinoic acid‐responsive gene, and is a novel growth differentiation factor. We examined the expression of the MK gene in specimens of 47 surgically removed human carcinomas of the gastrointestinal organs, namely, gastric, colorectal, hepatocellular, pancreatic, esophageal, ampullary duodenal and bile duct carcinomas. In most cases, the MK mRNA level was higher in cancer specimens than in the corresponding non‐cancerous tissues. Furthermore, MK mRNA was more highly expressed in the colon adenocarcinoma lesion than in the adenoma lesions, in the two familial polyposis cases. While MK mRNA was not detected in the normal liver, it became detectable in cirrhotic tissues in 2 of 4 cases, and its expression was increased in the cancerous tissues. Thus, the increase of MK mRNA level is a phenomenon seen in many human gastrointestinal carcinomas. The increased expression of the MK gene in gastric carcinoma was significantly more prominent in well and moderately differentiated adenocarcinomas than in poorly differentiated adenocarcinomas and signet ring cell carcinomas.

Objective: To determine the safety and cardiac chronotropic responsiveness to early atropine dobutamine stress echocardiography (DSE) in the elderly. Design: Retrospective study of 258 patients ⩾ 70 years who underwent early atropine DSE and 290 patients ⩾ 70 years who underwent conventional DSE. In the early atropine protocol, atropine was started at 20 μg/kg/min of dobutamine if heart rate was < 100 beats/min, up to 2 mg. The cardiac chronotropic responsiveness in the elderly was compared with a control group of patients < 70 years matched for sex, myocardial infarction, diabetes, and treatment with β blockers and calcium channel blockers. Results: The dose of dobutamine given to elderly patients was lower during early atropine than during conventional DSE (mean (SD) 29 (7) v 38 (4) μg/kg/min, p  =  0.001). Early atropine DSE resulted in diminished incidence of ventricular extrasystoles, non-sustained ventricular tachycardia, bradycardia, and hypotension compared with conventional DSE. In comparison with patients < 70 years, elderly patients required lower doses of dobutamine and atropine and achieved a higher percentage of predicted maximum heart rate (92 (9)% v 88 (10)%, p  =  0.0001). Except for more common hypotension (16% v 10%, p  =  0.004), no other difference in adverse effects was observed between patients ⩾ 70 and < 70 years. Conclusions: Early atropine DSE is a safe strategy in the elderly resulting in lower incidence of minor adverse effects than with the conventional protocol. Elderly patients presented adequate cardiac chronotropic responsiveness to early injections of atropine, requiring lower doses of drugs to reach test end points.

Objectives: To assess the accuracy of real-time myocardial contrast perfusion imaging (MCPI) for the diagnosis of restenosis and extent of coronary artery disease (CAD) in patients with previous percutaneous coronary intervention (PCI). Methods: 56 patients were studied 1.9 (SD 1.4) years after PCI. They underwent MCPI with commercially available ultrasound contrast agents (Optison or Definity) at rest and at peak dobutamine–atropine stress. Coronary angiography was performed within one month. Significant CAD was defined as ⩾ 50% stenosis in ⩾ 1 major epicardial coronary artery. Significant restenosis was defined as ⩾ 50% stenosis in a coronary segment with previous intervention. Results: Reversible perfusion abnormalities were detected in 40 of 43 patients with significant CAD and in 4 of 13 patients without (overall sensitivity 93%, 95% CI 85% to 99%; specificity 69%, 95% CI 44% to 94%; and accuracy 88%, 95% CI 79% to 96%). Significant restenosis in ⩾ 1 coronary artery with previous PCI was detected in 38 (68%) patients. Reversible perfusion abnormalities were present in 35 of them (sensitivity 92%, 95% CI 84% to 99%). Reversible perfusion abnormalities were detected in ⩾ 2 vascular distributions in 20 of 28 patients with multivessel CAD and in 3 of 28 patients without (sensitivity 71%, 95% CI 55% to 88%; specificity 89%, 95% CI 78% to 99%; and accuracy 80%, 95% CI 70% to 91%). Restenosis was detected in 41 coronary arteries. Sensitivity of MCPI for regional diagnosis of restenosis was 73% (95% CI 60% to 87%), specificity was 75% (95% CI 60% to 90%), and accuracy was 74% (95% CI 64% to 84%). Conclusion: Dobutamine stress MCPI is a useful technique for the evaluation of restenosis and extent of CAD after PCI.

The response of the North Atlantic thermohaline circulation to idealized climate forcing of 1% per year compound increase in CO₂ is examined in three configurations of the Community Climate System Model version 3 that differ in their component model resolutions. The strength of the Atlantic overturning circulation declines at a rate of 22%–26% of the corresponding control experiment maximum overturning per century in response to the increase in CO₂. The mean meridional overturning and its variability on decadal time scales in the control experiments, the rate of decrease in the transient forcing experiments, and the rate of recovery in periods of CO₂ stabilization all increase with increasing component model resolution. By examining the changes in ocean surface forcing with increasing CO₂ in the framework of the water-mass transformation function, we show that the decline in the overturning is driven by decreasing density of the subpolar North Atlantic due to increasing surface heat fluxes. While there is an intensification of the hydrologic cycle in response to increasing CO₂, the net effect of changes in surface freshwater fluxes on those density classes that are involved in deep-water formation is to increase their density; that is, changes in surface freshwater fluxes act to maintain a stronger overturning circulation. The differences in the control experiment overturning strength and the response to increasing CO₂ are well predicted by the corresponding differences in the water-mass transformation rate. Reduction of meridional heat transport and enhancement of meridional salt transport from mid to high latitudes with increasing CO₂ also act to strengthen the overturning circulation. Analysis of the trends in an ideal age tracer provides a direct measure of changes in ocean ventilation time scale in response to increasing CO₂. In the subpolar North Atlantic south of the Greenland–Scotland ridge system, there is a significant increase in subsurface ages as open-ocean deep convection is diminished and ventilation switches to a predominance of overflow waters. In middle and low latitudes there is a decrease in age within and just below the thermocline in response to a decrease in the upwelling of old deep waters. However, when considering ventilation within isopycnal layers, age increases for layers in and below the thermocline due to the deepening of isopycnals in response to global warming.