Editorial: Advancing our commitment to antiracist scholarship

Social work prides itself as a profession committed to improving the lives of people who are vulnerable, oppressed, and living in poverty. Achieving this mission requires candid conversations about racism as a social justice and public health issue and the role of social work in dismantling white supremacy and promoting racial justice. At its core, research on social work practice and policy should focus on examining how racism and inequality undermine the health, well-being, and social mobility of diverse and marginalized populations. We write this statement as a call to social work researchers to prioritize pursuits that will surface and motivate action to address the causes and consequences of racism. We also call on researchers to renew their commitment to scholarship that alleviates the suffering in Black, Indigenous, and other communities of color

Oracle-based optimization applied to climate model calibration

In this paper, we show how oracle-based optimization can be effectively used for the calibration of an intermediate complexity climate model. In a fully developed example, we estimate the 12 principal parameters of the C-GOLDSTEIN climate model by using an oracle- based optimization tool, Proximal-ACCPM. The oracle is a procedure that finds, for each query point, a value for the goodness-of-fit function and an evaluation of its gradient. The difficulty in the model calibration problem stems from the need to undertake costly calculations for each simulation and also from the fact that the error function used to assess the goodness-of-fit is not convex. The method converges to a Fbest fit_ estimate over 10 times faster than a comparable test using the ensemble Kalman filter. The approach is simple to implement and potentially useful in calibrating computationally demanding models based on temporal integration (simulation), for which functional derivative information is not readily available

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation

Parameter estimation in an intermediate complexity earth system model using an ensemble Kalman filter

We describe the development of an efficient method for parameter estimation and ensemble forecasting in climate modelling. The technique is based on the ensemble Kalman filter and is several orders of magnitude more efficient than many others which have been previously used to address this problem. As well as being theoretically (near-)optimal, the method does not suffer from the 'curse of dimensionality' and can comfortably handle multivariate parameter estimation. We demonstrate the potential of this method in identical twin testing with an intermediate complexity coupled AOGCM. The model's climatology is successfully tuned via the simultaneous estimation of 12 parameters. Several minor modifications arc described by which the method was adapted to a steady state (temporally averaged) case. The method is relatively simple to implement, and with only O(50) model runs required, we believe that optimal parameter estimation is now accessible even to computationally demanding models

Basal conditions of two Transantarctic Mountain outlet glaciers from observation-constrained diagnostic modelling

We present a diagnostic glacier flowline model parameterized and constrained by new velocity data from ice-surface GPS installations and speckle tracking of TerraSAR-X satellite images, newly acquired airborne-radar data, and continental gridded datasets of topography and geothermal heat flux, in order to better understand two outlet glaciers of the East Antarctic ice sheet. Our observational data are employed as primary inputs to a modelling procedure that first calculates the basal thermal regime of each glacier, then iterates the basal sliding coefficient and deformation rate parameter until the fit of simulated to observed surface velocities is optimized. We find that the two glaciers have both frozen and thawed areas at their beds, facilitating partial sliding. Glacier flow arises from a balance between sliding and deformation that fluctuates along the length of each glacier, with the amount of sliding typically varying by up to two orders of magnitude but with deformation rates far more constant. Beardmore Glacier is warmer and faster-flowing than Skelton Glacier, but an up-glacier deepening bed at the grounding line, coupled with ice thicknesses close to flotation, lead us to infer a greater vulnerability of Skelton Glacier to grounding-line recession if affected by ocean-forced thinning and concomitant acceleration

Grounding-zone ice thickness from InSAR: inverse modelling of tidal elastic bending

Ice-thickness measurements in Antarctic ice-shelf grounding zones are necessary for calculating the mass balance of individual catchments, but remain poorly constrained for most of the continent. We describe a new inverse modelling optimization approach to estimate ice thickness in the grounding zone of Antarctic outlet glaciers and ice shelves using spatial patterns of tide-induced flexure derived from differential interferometric synthetic aperture radar (InSAR). We demonstrate that the illposedness of the inverse formulation of the elastic-plate equations for bending can be controlled by regularization. In one dimension, the model recreates smooth, synthesized profiles of ice thickness from flexure information to within 1–2%. We test the method in two dimensions and validate it in the grounding zone of Beardmore Glacier, a major outlet glacier in the Transantarctic Mountains, using interferograms created from TerraSAR-X satellite imagery acquired in 2012. We compare our results with historic and modern ice-thickness data (radio-echo sounding from 1967 and ground-penetrating radar from 2010). We match both longitudinal and transverse thickness transects to within 50m root mean-square error using an effective Young’s modulus of 1.4GPa. The highest accuracy is achieved close to the grounded ice boundary, where current estimates of thickness based on surface elevation measurements contain a systematic bias towards thicker ice

Effects of atmospheric dynamics and ocean resolution on bi-stability of the thermohaline circulation examined using the Grid ENabled Integrated Earth system modelling (GENIE) framework

We have used the Grid ENabled Integrated Earth system modelling (GENIE) framework to undertake a systematic search for bi-stability of the ocean thermohaline circulation (THC) for different surface grids and resolutions of 3-D ocean (GOLDSTEIN) under a 3-D dynamical atmosphere model (IGCM). A total of 407,000 years were simulated over a three month period using Grid computing. We find bi-stability of the THC despite significant, quasi-periodic variability in its strength driven by variability in the dynamical atmosphere. The position and width of the hysteresis loop depends on the choice of surface grid (longitude-latitude or equal area), but is less sensitive to changes in ocean resolution. For the same ocean resolution, the region of bi-stability is broader with the IGCM than with a simple energy-moisture balance atmosphere model (EMBM). Feedbacks involving both ocean and atmospheric dynamics are found to promote THC bi-stability. THC switch-off leads to increased import of freshwater at the southern boundary of the Atlantic associated with meridional overturning circulation. This is counteracted by decreased freshwater import associated with gyre and diffusive transports. However, these are localised such that the density gradient between North and South is reduced tending to maintain the THC off state. THC switch-off can also generate net atmospheric freshwater input to the Atlantic that tends to maintain the off state. The ocean feedbacks are present in all resolutions, across most of the bi-stable region, whereas the atmosphere feedback is strongest in the longitude–latitude grid and around the transition where the THC off state is disappearing. Here the net oceanic freshwater import due to the overturning mode weakens, promoting THC switch-on, but the atmosphere counteracts this by increasing net freshwater input. This increases the extent of THC bi-stability in this version of the model

GENIE: Delivering e-Science to the environmental scientist

The GENIE project aims to deliver a Grid-based, modular, distributed and scalable Earth System Model for long-term and paleo-climate studies to the environmental sciences community. In this paper we address the scientific problem of the vulnerability of the thermohaline circulation to the global climate, and describe our e-scientific solution using a Grid-based architecture involving Condor computational resources, web service oriented data management mechanisms and the employment of a web portal. We find that the scientific results of our e-science efforts are useful to the environmental science community, and provide a means of fulfilling the longer-term aims of the GENIE project

A Decentralized Calendar System Featuring Sharing, Trusting and Negotiating

International audienceThis article presents a decentralized calendar system benefiting from the use of computational trust. In our system, each user is represented by an agent in charge of the scheduling of events, either tasks or meetings. Each event is characterized by two attributes: importance and urgency. These notions are subjective: each agent has its own priorities and its own view of what is important and urgent. Timetables can be shared with other agents according to the groups of the agents, thus facilitating the scheduling of a meeting within a group. Nevertheless, timetables do not have to be shared. So we introduce trust to support this absence of information. These mechanisms use a generic trust model permitting the calculation of trust from several sources. We stress on the importance of the different sources for the emergence of trust groups. When trust is not given between all participants in a meeting, negotiation is used to find a possible date