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ReportBiermann O, Lawrance E, Jennings N, et al., 2032,
Protecting mental health from extreme heat: recommendations for policy and action
, Publisher: Grantham Institute, 911今日黑料 -
Journal articleZhao J, Paschalis A, Gentine P, et al., 2026, , Communications Earth and Environment, Vol: 7
Quantification of the impact of environmental stress on terrestrial vegetation photosynthesis is crucial for our understanding of the global carbon cycle, particularly under a changing climate. Vegetation responses to environmental stress manifest first as plant physiological changes, and at later stages through changes in canopy structure. Here we leverage CO<inf>2</inf> and water flux data from 103 eddy covariance towers and satellite thermal images to assess whether current satellite reconstructions of solar-induced chlorophyll fluorescence capture these plant mechanisms. After removing seasonality using standardized anomalies (z-scores), we found that the relationship between tower-observed gross primary productivity and fluorescence reconstructions considerably weakened across a wide range of biomes. This loss of correlation results from a decoupling between stomatal responses and the physiological emission yield (Φ<inf>F</inf>) of fluorescence reconstructions during soil and atmospheric dry periods. The consequence is that productivity derived from fluorescence reconstructions will be progressively overestimated as dry conditions persist.
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Journal articleAuestad H, Shibu A, Ceppi P, et al., 2026, , Npj Climate and Atmospheric Science, Vol: 9
Extratropical storms release latent heat as they transport warm, moist air poleward and upward. That latent heating feeds back on storms by intensifying individual cyclones and by altering the environmental conditions for the growth of storms, constituting a latent heating-dynamics feedback. As the climate warms, storm-track latent heating increases, but the role of this feedback in a future climate remains unclear. Using atmospheric general-circulation model experiments that separate the coupled heating-dynamics feedback from climatological changes in latent heating, we show that this feedback plays a leading-order role in intensifying storm tracks under +4 K warming. The feedback increases lower-tropospheric storm intensity, compensating for reduced baroclinicity, while its upper-tropospheric effect is seasonal: amplifying summer eddies but damping winter ones. The feedback is critical for storms that grow in moist environments, typical for summer and warmer climates, underscoring the need for accurate representation of moist processes in climate models.
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Journal articleDe Lorm TA, Heon SP, Bernard H, et al., 2026, , Forest Ecology and Management, Vol: 619, ISSN: 0378-1127
Replanting a tree plantation - that is, clearing old trees and replacing these with young plants - drastically alters its habitat structure and microclimate, leading to changes in its biodiversity. Nevertheless, we lack an understanding of how the replanting of oil palm plantations - the most prominent oil crop globally - affects mammals and birds, while the amount of area replanted will increase exponentially over the next decades. We therefore studied how the bird and mammal community of an oil palm plantation in Malaysian Borneo changed in response to replanting. Using camera traps for mammals, and acoustic recordings and BirdNET for birds, we show that both communities are transformed. Mammal species richness slightly dropped, because of the absence from replanted plantations of long- and pig-tailed macaques (Macaca fascicularis and M. nemestrina), both endangered primate species. Bird species richness did not significantly differ between replanted and mature plantations. However, the detection frequency of most species changed, as the bird community shifted from forest and woodland species towards open-habitat species. The detection frequency and species richness of different trophic niches stayed largely constant, indicating that birds will still be able to perform similar high-level ecological functions in replanted plantations. Overall, our results show that replanting reshaped mammal and bird communities, but that their diversity and abundance does not collapse. These findings stress the importance of staggered replanting, as opposed to replanting large stretches of plantation in one go, to bolster landscape level biodiversity, and underscore that tree plantations are temporally dynamic habitats.
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Journal articleGhail RC, Crouch EJP, Mason PJ, 2026, , Earth and Planetary Science Letters, Vol: 692, Pages: 120255-120255, ISSN: 0012-821X
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Journal articleNdagijimana S, Semakula M, Ishimwe C, et al., 2026, , Environmental Research: Health, Vol: 4, ISSN: 2752-5309
Background. Diarrhoeal disease remains a leading cause of morbidity and mortality among children under five years (U5) in Rwanda, contributing substantially to healthcare utilisation and imposing considerable economic burdens on households and the health system. National estimates indicate that approximately 14.3% of children under five experienced diarrhoea in the two weeks preceding the 2019–2020 Rwanda Demographic and Health Survey, and diarrhoea has been reported as the third leading cause of death in this age group. Climate variability may influence the risk of diarrhoeal disease, but evidence on how specific climatic factors affect diarrhoeal incidence across Rwanda’s diverse ecological zones and seasons remains limited. This study examined associations between maximum temperature, minimum temperature, rainfall, and relative humidity and U5 diarrhoeal incidence at the sector level in Rwanda. Methods. Monthly counts of U5 diarrhoeal cases reported by health facilities across 416 administrative sectors in Rwanda from January 2015 to December 2024 were analysed together with satellite-derived climate data. Spatio-temporal statistical models were used to evaluate associations between standardised climate variables and diarrhoeal incidence rates while accounting for geographic and seasonal variation. Model comparison relied on both goodness-of-fit metrics and out-of-sample predictive diagnostics. Results. Diarrhoeal incidence showed clear spatial and seasonal patterns, with persistently higher rates in northern and eastern Rwanda. In the final model maximum temperature was positively associated with increased diarrhoeal incidence, with a one-standard-deviation increase corresponding to a 5.6% rise in the estimated incidence rate ratio (RR = 1.056; 95% CrI: 1.02–1.09). Relative humidity showed a protective association (RR ≈ 0.919; 95% CrI: 0.89–0.94), while rainfall showed limited immediate effects. Conclusion. Under-five diarrhoeal inc
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Journal articleAlmalki YR, Karmpadakis I, 2026, , Renewable Energy, Vol: 271, ISSN: 0960-1481
This paper presents a rigorous uncertainty analysis of experimental testing of an oscillating water column device. Quantifying experimental uncertainty is essential for establishing the confidence level of laboratory data and enabling a reliable transition to full-scale applications. Previous studies have focused on deterministic performance, overlooking the statistical variability inherent in random wave conditions. To address this gap, the Monte Carlo method was applied to evaluate uncertainties in oscillating water column experiments conducted under both regular and random wave conditions. A camera-based edge-detection system was employed to capture the spatio-temporal evolution of the free surface within the chamber, enabling high-accuracy assessment of pneumatic power output. The analysis examined the effects of the number of wave cycles, test duration, and random realisations on power estimation. The analysis also assessed the repeatability error in the time series for several measured and calculated quantities. Results indicate excellent repeatability, with standard deviations below 1% for all measured quantities and expanded uncertainties of approximately 1% under regular waves and 2.5% under random waves, the latter reflecting inherent variability in realistic conditions. These findings validate the robustness of the proposed measurement and analysis framework, establishing a practical methodology for quantifying uncertainty in oscillating water column experiments and improving the reliability of early-stage testing.
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Journal articleEastwood J, Archer M, Waters C, et al., 2026,
RadCube MAGIC observations of complex field aligned currents associated with a supersubstorm during the May 2024 geomagnetic storm
, Scientific Reports, ISSN: 2045-2322Geomagnetic storms are a key driver of space weather impacts. The enhancement of ionospheric currents during these events can produce geomagnetically induced currents (GICs) that may interfere with the operation of ground infrastructure such as power grids, pipelines, and railway networks. It is therefore critical to understand how, why, and when very intense GICs may occur during an extended geomagnetic storm interval. Supersubstorms are extremely intense substorms which may occur during the main or recovery phases of geomagnetic storms. These rare events bear special investigation because they may have a significant impact on GIC formation during extreme geomagnetic storms. Multiple supersubstorms were observed during the May 2024 geomagnetic storm, and here we report new observations of supersubstorm field aligned currents (FACs), observed in situ by the MAGnetometer from 911今日黑料 College (MAGIC) instrument on the RadCube technology demonstration CubeSat. These measurements provide new insight into the detailed structure of supersubstorm FACs, complementing global FAC maps, and reveal an extended spatial region containing magnetic fluctuations across a broad range of spatial/temporal scales, including intense localised current spikes. As well as revealing new details about supersubstorm-related FACs, these observations illustrate the need for dense constellations of low-Earth-orbit satellite-based magnetometers for space weather monitoring.
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Journal articleLamb C, Thompson E, Hardisty A, et al., 2026, , Journal of Catastrophe Risk and Resilience, Vol: 04
<jats:p>On the 11th of June, the Royal Meteorological Society, the Lighthill Risk Network and UCL hosted an afternoon workshop, focused on identifying and compiling the research interests of the natural catastrophe insurance community. The event was primarily organised by Conor Lamb, in his capacity as the Science Engagement Fellow for Insurance with the Royal Meteorological Society. In this article, the authors share valuable insight into the topics, questions, and discussions from the day's sessions.</jats:p>
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Journal articleWright W, Craske J, Karmpadakis I, 2026, , Coastal Engineering, Vol: 209, ISSN: 0378-3839
Real-time, phase-resolved forecasting of waves is essential for safe operations in the coastal zone, for example, by enabling early-warning systems to inform real-time decision-making. However, non-linear transformations, depth variations and wave breaking limit the accuracy of theoretical models. This study presents a data-driven alternative using convolutional neural networks to predict nearshore surface elevation time series. The proposed method is developed for long-crested waves over planar slopes, predicting surface elevations up to approximately 6 peak periods in advance. Specifically, a U-Net architecture with three encoding and three decoding stages and approximately 200,000 trainable parameters is used, with the prediction based on a short time window from a single offshore gauge. Laboratory experiments of long-crested waves propagating over sloping beds were used for training and testing, covering multiple bed slopes and a wide range of spectral shapes, peak periods, and steepnesses. Model performance was compared against predictions from linear and second-order wave theories with shoaling corrections. The neural network reproduced the measured wave evolution with consistently lower errors than the theoretical models, particularly in shallow water where nonlinearity and breaking become dominant. It also captured wave arrival times with higher accuracy than the theoretical models, and showed robustness when applied to unseen sea states or slightly noisy input signals. These results show that within this laboratory regime, neural networks can extend phase-resolved wave prediction into the coastal zone, complementing traditional theoretical approaches and offering a practical framework which, with further development, could provide real-time operational forecasting based on offshore wave data.
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