Over the coming decades, it is expected that the spatial pattern of anthropogenic aerosol will change dramatically and the global aerosol composition will become relatively more absorbing. Yet, the climatic impact of this evolving spatial pattern of absorbing aerosol has received relatively little attention, in particular its impact on global-mean effective radiative forcing. Here, using model experiments, we show that the effective radiative forcing from absorbing aerosol varies strongly depending on their location, driven by rapid adjustments of clouds and circulation. Our experiments generate positive effective radiative forcing in response to aerosol absorption throughout the midlatitudes and most of the tropical regions, and a strong ‘hot spot’ of negative effective radiative forcing in response to aerosol absorption over the tropical Western Pacific. Further, these diverse responses can be robustly attributed to changes in atmospheric dynamics and highlight the importance of this ‘aerosol pattern effect’ for transient forcing from regional biomass-burning aerosol.

BackgroundDespite the great burden of chronic respiratory diseases in China, few large multicentre, spirometry-based studies have examined its prevalence, rate of underdiagnosis regionally or the relevance of socioeconomic and lifestyle factors.MethodsWe analysed data from 512 891 adults in the China Kadoorie Biobank, recruited from 10 diverse regions of China during 2004–2008. Air flow obstruction (AFO) was defined by the lower limit of normal criteria based on spirometry-measured lung function. The prevalence of AFO was analysed by region, age, socioeconomic status, body mass index (BMI) and smoking history and compared with the prevalence of self-reported physician-diagnosed chronic bronchitis or emphysema (CB/E) and its symptoms.FindingsThe prevalence of AFO was 7.3% in men (range 2.5–18.2%) and 6.4% in women (1.5–18.5%). Higher prevalence of AFO was associated with older age (p<0.0001), lower income (p<0.0001), poor education (p<0.001), living in rural regions (p<0.001), those who started smoking before the age of 20 years (p<0.001) and low BMI (p<0.001). Compared with self-reported diagnosis of CB/E, 88.8% of AFO was underdiagnosed; underdiagnosis proportion was highest in 30–39-year olds (96.7%) compared with the 70+ age group (81.1%), in women (90.7%), in urban areas (89.4%), in people earning 5K–10 K ¥ monthly (90.3%) and in those with middle or high school education (92.6%).InterpretationIn China, the burden of AFO based on spirometry was high and significantly greater than that estimated based on self-reported physician-diagnosed CB/E, especially in rural areas, reflecting major issues with diagnosis of AFO that will impact disease treatment and management.

Abstract. Large computer models are ubiquitous in the Earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties, and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case studies using ESEm to reduce parametric uncertainty in a general circulation model and explore precipitation sensitivity in a cloud-resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.

Background Joint injury is a major risk factor for osteoarthritis and provides an opportunity to prospectively examine early processes associated with osteoarthritis. We investigated whether predefined baseline demographic and clinical factors, and protein analytes in knee synovial fluid and in plasma or serum, were associated with clinically relevant outcomes at 2 years after knee injury.Methods This longitudinal cohort study recruited individuals aged 16-50 years between Nov 1, 2010, and Nov 28, 2014, across six hospitals and clinics in London, UK. Participants were recruited within 8 weeks of having a clinically significant acute knee injury (effusion and structural injury on MRI), which was typically treated surgically. We measured several predefined clinical variables at baseline (eg, time from injury to sampling, extent and type of joint injury, synovial fluid blood staining, presence of effusion, self-reported sex, age, and BMI), and measured 12 synovial fluid and four plasma or serum biomarkers by immunoassay at baseline and 3 months. The primary outcome was Knee Injury and Osteoarthritis Outcome Score (KOOS 4 ) at 2 years, adjusted for baseline score, assessed in all patients. Linear and logistic regression models adjusting for predefined covariates were used to assess associations between baseline variables and 2-year KOOS 4 . This study is registered with ClinicalTrials.gov, number NCT02667756. FindingsWe enrolled 150 patients at a median of 17 days (range 1-59, IQR 9-26) after knee injury. 123 (82%) were male, with a median age of 25 years (range 16-50, IQR 21-30). 98 (65%) of 150 participants completed a KOOS 4 at 2 (or 3) years after enrolment (50 participants were lost to follow-up and two were withdrawn due to adverse events unrelated to study participation); 77 (51%) participants had all necessary variables available and were included in the core variable adjusted analysis. In the 2-year dataset mean KOOS 4 improved from 38 (SD 18) at baseline to 79 (18) at 2 years. Baseline KOOS 4, medium-to-large knee effusion, and moderate-to-severe synovial blood staining and their interaction significantly predicted 2-year KOOS 4 (n=77; coefficient -20•5, 95% CI -34•8 to -6•18; p=0•0060). The only predefined biomarkers that showed independent associations with 2-year KOOS 4 were synovial fluid MCP-1 (n=77; -0•015, 0•027 to -0•004 per change in 1 pg/mL units; p=0•011) and IL-6 (n=77; -0•0005, -0•0009 to -0•0001 per change in 1 pg/mL units; p=0•017). These biomarkers, combined with the interaction of effusion and blood staining, accounted for 39% of outcome variability. Two adverse events occurred that were linked to study participation, both at the time of blood sampling (one presyncopal episode, one tenderness and pain at the site of venepuncture).Interpretation The combination of effusion and haemarthrosis was significantly associated with symptomatic outcomes after acute knee injury. The synovial fluid molecular protein response to acute knee injury (best represented by MCP-1 and IL-6) was independently as...

Using model simulations, we demonstrate that the climate response to localized tropical sea surface temperature (SST) perturbations exhibits numerous non‐linearities. Most pronounced is an asymmetry in the response to positive and negative SST perturbations. Additionally, we identify a “magnitude‐dependence” of the response on the size of the SST perturbation. We then explain how these non‐linearities arise as a robust consequence of convective quasi‐equilibrium and weak (but non‐zero) temperature gradients in the tropical free‐troposphere, which we encapsulate in a “circus tent” model of the tropical atmosphere. These results demonstrate that the climate response to SST perturbations is fundamentally non‐linear, and highlight potential deficiencies in work which has assumed linearity in the response.