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Abstract Extreme weather and coronavirus-type pandemics are both leading global health concerns. Until now, no study has quantified the compound health consequences of the co-occurrence of them. We estimate the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality. We show that temperature-related mortality exceeded COVID-19 mortality by 8% in South West England. Combined, extreme temperatures and COVID-19 led to 19 (95% confidence interval: 16–22 in North West England) to 24 (95% confidence interval: 20–29 in Wales) excess deaths per 100,000 population during heatwaves, and 80 (95% confidence interval: 75–86 in Yorkshire and the Humber) to 127 (95% confidence interval: 123–132 in East of England) excess deaths per 100,000 population during cold snaps. These numbers are at least ~2 times higher than the previous decade. Society must increase preparedness for compound health crises such as extreme weather coinciding with pandemics.

Abstract The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2–50] times more likely. At the current rate of global warming, the likelihood of such an event is doubling every 20 [10–50] years. Given the multi-decade lower-bound return-time implied by the length of the historical record, this rate of change in likelihood is highly relevant for decision makers. Further, forecast-based attribution can synthesise the conditional event-specific storyline and unconditional event-class probabilistic approaches to attribution. If developed as a routine service in forecasting centres, it could provide reliable estimates of human influence on extreme weather risk, which is critical to supporting effective adaptation planning.

America is a paradox: one of the world's economically leading countries, lagging in sustainable development (SD). Drawing on many studies, the problems caused by imbalances between the environment and economy often result in resource drains at the local level, leaving the state and local government officials to devise solutions to address such imbalances. While there are a few UN studies available analyzing this phenomenon at the state scale, no studies have observed SDGs across 3,142 localities (counties or county-equivalents) within the USA. The study categorized these SDGs into three pillars of SD: Social, Economic, and Environmental, to analyze the balance and imbalance between the pillars of SD across all states and localities within the USA. An indicator-based approach was used to measure SDGs for the years 2010 and 2015. Results confirmed the uniform distribution of overall SDG Index distribution across states, but some localities performed poorly, mainly in the Southern Region. Rank-wise, top scorers upheld balanced scores across three pillars and bottom ranks showed imbalances. Overall, the social pillar was less predominant, but the economic and environmental pillars predominated in the northern and southern parts of the nation, respectively. The outcome of the study can help collaborate and build networks, targeting clustered areas through collective actions and planning local strategies for the outliers and other localities. While localization is the key, balancing between three pillars is essential to make progress on the path of SD. Therefore, the present study can be used as a framework to prioritize SDG actions at sub-national scales.

Abstract Observed rapid Arctic warming and sea‐ice loss are likely to continue in the future, unless and after greenhouse gas emissions are reduced to net‐zero. Here, we examine the possible effects of future sea‐ice loss at 2°C global warming above pre‐industrial levels on winter temperature extremes across the Northern Hemisphere, using coordinated experiments from the Polar Amplification Model Intercomparison Project. 1‐in‐20‐year cold extremes are simulated to become less severe at high‐ and mid‐latitudes in response to Arctic sea‐ice loss. 1‐in‐20‐year winter warm extremes become warmer at northern high latitudes due to sea‐ice loss, but warm by less than cold extremes. We compare the response to sea‐ice loss to that from global sea surface temperature (SST) change also at 2°C global warming. SST change causes less severe cold extremes and more severe warm extremes globally. Except northern high latitudes, the response to SST change is of larger magnitude than that to Arctic sea‐ice loss.

Sudden stratospheric warmings (SSWs) have been linked to surface temperature anomalies, but how these connect to changes in the likelihood of specific weather extremes and their associated weather patterns remains uncertain. While, on average, it is true that cold surface temperatures follow SSW events, particularly in Northern Europe, there is considerable event-to-event variability. Over the British Isles and Central Europe, only around 45% of SSWs are followed by a colder than average period and a negative phase of the North Atlantic Oscillation, cautioning against an over-generalised approach to surface anomalies associated with SSWs. Focussing on more hazardous weather, which in winter is associated with cold extremes, we use reanalysis data to consider how SSWs impact temperature-related hazards; namely the frequency of snowy days, frost days and spells of extreme cold weather in 12 major European cities. In general, SSWs are associated with an increased risk of snow across most of western Europe, and that this is particularly significant in milder, more maritime locations such as London where in reanalysis, snowfall days are 40% more likely after an SSW. However, there is considerable variation in surface temperature anomalies between SSW events; the third of SSWs with the warmest surface anomalies are statistically more likely to have a decreased risk of snow, frost and persistent cold spells compared with non-SSW time periods. These warmer events are associated with a different temperature anomaly pattern, which is consistent in both reanalysis data and large ensemble CMIP6 models. We further show that these warm surface temperature anomaly SSWs are becoming more frequent, a trend which is consistent with background global warming. The varied surface anomalies associated with SSWs highlights the need to study their impacts in a probabilistic sense, and motivates further work to enable better prediction of the impacts of a given event.

Heatwaves are a serious threat to human life. Public health agencies that are responsible for delivering heat-health action plans need to assess and reduce the mortality impacts of heat. Statistical models developed in epidemiology have previously been used to attribute past observed deaths to high temperatures and project future heat-related deaths. Here, we investigate the novel use of summer temperature-mortality associations established by these models for monitoring heat-related deaths in regions in England in near real time. For four summers in the period 2011–2020, we find that coupling these associations with observed daily mean temperatures results in England-wide heatwave mortality estimates that are consistent with the excess deaths estimated by UK Health Security Agency. However, our results for 2013, 2018 and 2020 highlight that the lagged effects of heat and characteristics of individual summers contribute to disagreement between the two methods. We suggest that our method can be used for heatwave mortality monitoring in England because it has the advantages of including lagged effects and controlling for other risk factors. It could also be employed by health agencies elsewhere for reliably estimating the health burden of heat in near real time and near-term forecasts.

Summer heat extremes in the UK pose a risk to health (amongst other sectors) and this is exacerbated by localised socio-economic factors that contribute to vulnerability. Here, regional climate model simulations from the UK Climate Projections are used to assess how different elements of extreme heat will vary across the UK in the future under global mean surface temperature warming levels of +1.5 °C, +2.0 °C and +3.0 °C above pre-industrial. Heat stress metrics incorporating daily maximum and minimum temperature, temperature variability and vapour pressure are included. These show qualitatively similar spatial patterns for the recent past, with the most pronounced heat hazards found in south-eastern regions of the UK. Projected heat hazard changes across the UK are not homogeneous, with southern regions (e.g. Greater London, South East) showing greater increases in maximum temperatures and northern regions (e.g. Scotland and Northern Ireland) showing greater increases in humidity. With +3.0 °C warming, the relative change in combined heat hazards is found to be greatest in the south-western UK, however, in absolute terms, south-eastern regions will still experience the greatest hazards. When combined with socio-economic factors, hotspots of high heat stress risk emerge in parts of London, the Midlands and eastern England along with southern and eastern coastal regions. Weighting of different heat risk factors is subjective and to this end we have developed and made available an interactive app which allows users to assess sensitivities and uncertainties in the projected UK heat risk.

Tropospheric and stratospheric tropical temperature trends in recent decades have been notoriously hard to simulate using climate models, particularly in the upper troposphere. Aside from the warming trend itself, this has broader implications, e.g. atmospheric circulation trends depend on latitudinal temperature gradients. In this study, tropical temperature trends in the CMIP6 models are examined, from 1979 to 2014, and contrasted with trends from the RICH/RAOBCORE radiosondes, and the ERA5/5.1 reanalysis. As in earlier studies, we find considerable warming biases in the CMIP6 modeled trends, and we show that these biases are linked to biases in surface temperature. We also uncover previously undocumented biases in the lower-middle stratosphere: the CMIP6 models appear unable to capture the time evolution of stratospheric cooling, which is non-monotonic owing to the Montreal Protocol. Finally, using models with large ensembles, we show that their standard deviation in tropospheric temperature trends, which is due to internal variability alone, explains ∼ 50% (± 20%) of that from the CMIP6 models.

Extreme weather and coronavirus-type pandemics are both leading global health concerns. Until now, no study has quantified the compound health consequences of the co-occurrence of them. We estimate the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality. We show that temperature-related mortality exceeded COVID-19 mortality by 8% in South West England. Combined, extreme temperatures and COVID-19 led to 19 (95% confidence interval: 16-22 in North West England) to 24 (95% confidence interval: 20-29 in Wales) excess deaths per 100,000 population during heatwaves, and 80 (95% confidence interval: 75-86 in Yorkshire and the Humber) to 127 (95% confidence interval: 123-132 in East of England) excess deaths per 100,000 population during cold snaps. These numbers are at least ~2 times higher than the previous decade. Society must increase preparedness for compound health crises such as extreme weather coinciding with pandemics. [ABSTRACT FROM AUTHOR]

Abstract: Patients with sickle cell disease (SCD) are at elevated risk of silent cerebral infarcts and strokes; however, they frequently lack established stroke risk factors (eg, macrovascular arterial steno-occlusion) and the mechanisms underlying such events are incompletely characterized. This study evaluated cerebral hemometabolism with respect to imaging markers of vascular shunting in 143 participants with SCD, including 73 pediatric (aged 6-17 years) and 70 adult (aged 18-40 years) participants using 3-Tesla brain magnetic resonance imaging (MRI). Vascular shunting was assessed in each patient using a previously published ordinal venous hyperintensity score (VHS) of 0, 1, or 2 on cerebral blood flow-weighted MRI. Participants with VHS of 2, indicative of the most rapid arteriovenous transit, had significantly reduced blood oxygen content (CaO2; 10.90 ± 1.69 mL O2/100 mL blood), oxygen extraction fraction (OEF; 33.52% ± 5.54%), and cerebral metabolic rate of oxygen consumption (CMRO2; 2.91 ± 0.69 mL O2/100 g tissue per minute) compared with their counterparts with VHS = 0 (CaO2 = 12.42 ± 1.58 mL O2/100 mL blood; OEF = 39.03% ± 3.80%; CMRO2 = 3.77 ± 0.84 mL O2/100 g tissue per minute) or VHS = 1 (CaO2 = 11.86 ± 1.73 mL O2/100 mL blood; OEF = 36.37% ± 5.11%; CMRO2 = 3.59 ± 0.78 mL O2/100 g tissue per minute). Both pediatric and adult patients with SCD presenting with greater imaging evidence of vascular shunting had mildly reduced OEF and CMRO2. These findings highlight that imaging markers of vascular shunting are associated with significant, albeit mild, evidence of reduced OEF and CMRO2 in patients with SCD.

Combined heat and humidity is frequently described as the main driver of human heat‐related mortality, more so than dry‐bulb temperature alone. While based on physiological thinking, this assumption has not been robustly supported by epidemiological evidence. By performing the first systematic comparison of eight heat stress metrics (i.e., temperature combined with humidity and other climate variables) with warm‐season mortality, in 604 locations over 39 countries, we find that the optimal metric for modelling mortality varies from country to country. Temperature metrics with no or little humidity modification associates best with mortality in ~40% of the studied countries. Apparent temperature (combined temperature, humidity and wind speed) dominates in another 40% of countries. There is no obvious climate grouping in these results. We recommend, where possible, that researchers use the optimal metric for each country. However, dry‐bulb temperature performs similarly to humidity‐based heat stress metrics in estimating heat‐related mortality in present‐day climate. [ABSTRACT FROM AUTHOR]

The reality of human-induced climate change is unequivocal and exerts an ever-increasing global impact. Access to the latest scientific information on current climate change and projection of future trends is important for planning adaptation measures and for informing international efforts to reduce emissions of greenhouse gases (GHGs). Identification of hazards and risks may be used to assess vulnerability, determine limits to adaptation, and enhance resilience to climate change. This article highlights how recent research programs are continuing to elucidate current processes and advance projections across major climate systems and identifies remaining knowledge gaps. Key findings include projected future increases in monsoon rainfall, resulting from a changing balance between the rainfall-reducing effect of aerosols and rainfall-increasing GHGs; a strengthening of the storm track in the North Atlantic; an increase in the fraction of precipitation that falls as rain at both poles; an increase in the frequency and severity of El Niño Southern Oscillation (ENSO) events, along with changes in ENSO teleconnections to North America and Europe; and an increase in the frequency of hazardous hot-humid extremes. These changes have the potential to increase risks to both human and natural systems. Nevertheless, these risks may be reduced via urgent, science-led adaptation and resilience measures and by reductions in GHGs.