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Journal articleZhao J, Paschalis A, Gentine P, et al., 2026,
Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses
, Communications Earth and Environment, Vol: 7Quantification 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 articleWang Y, Warder SC, Benmoufok EF, et al., 2026,
Geographic variability in reanalysis wind speed biases: A high-resolution bias correction approach for UK wind energy
, Energy Conversion and Management, Vol: 352, ISSN: 0196-8904Reanalysis datasets have become indispensable tools for wind resource assessment and wind power simulation, offering long-term and spatially continuous wind fields across large regions. However, they inherently contain systematic wind speed biases arising from various factors, including simplified physical parameterizations, observational uncertainties, and limited spatial resolution. Among these, low spatial resolution poses a particular challenge for capturing local variability accurately. Whereas prevailing industry practice generally relies on either no bias correction or coarse, nationally uniform adjustments, we extend and thoroughly analyse a recently proposed spatially resolved, cluster-based bias correction framework. This approach is designed to better account for local heterogeneity and is applied to 319 wind farms across the United Kingdom to evaluate its effectiveness. Results show that this method reduced monthly wind power simulation errors by more than 32% compared to the uncorrected ERA5 reanalysis dataset. The method is further applied to the MERRA-2 dataset for comparative evaluation, demonstrating its effectiveness and robustness for different reanalysis products. In contrast to prior studies, which rarely quantify the influence of topography on reanalysis biases, this research presents a detailed spatial mapping of bias correction factors across the UK. The analysis reveals that for wind energy applications, ERA5 wind speed errors exhibit strong spatial variability, with the most significant underestimations in the Scottish Highlands and mountainous areas of Wales. These findings highlight the importance of explicitly accounting for geographic variability when correcting reanalysis wind speeds, and provide new insights into region-specific bias patterns relevant for high-resolution wind energy modelling.
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Journal articleFargette N, Eastwood JP, Phan TD, et al., 2026,
Fluid and Kinetic Properties of the Near-Sun Heliospheric Current Sheet
, The Astrophysical Journal, Vol: 997, Pages: 174-174, ISSN: 0004-637X<jats:title>Abstract</jats:title> <jats:p> The heliospheric current sheet (HCS) is an important large-scale structure of the heliosphere, and, for the first time, the Parker Solar Probe (PSP) mission enables us to study its properties statistically, close to the Sun. We visually identify the 39 HCS crossings measured by PSP below 50 <jats:italic>R</jats:italic> <jats:sub>⊙</jats:sub> during encounters 6–21, and investigate the occurrence and properties of magnetic reconnection, the behavior of the spectral properties of the turbulent energy cascade, and the occurrence of kinetic instabilities at the HCS. We find that 82% of the HCS crossings present signatures of reconnection jets, showing that the HCS is continuously reconnecting close to the Sun. The proportion of inward and outward jets depends on heliocentric distance, and the main HCS reconnection X-line has a higher probability of being located close to the Alfvén surface. We also observe a radial asymmetry in jet acceleration, where inward jets do not reach the local Alfvén speed, contrary to outward jets. We find that turbulence levels are enhanced in the ion kinetic range, consistent with the triggering of an inverse cascade by magnetic reconnection. Finally, we highlight the ubiquity of magnetic hole trains in the high- <jats:italic>β</jats:italic> environment of the HCS, showing that the mirror mode instability plays a key role in regulating the ion temperature anisotropy in HCS reconnection. Our findings shed new light on the properties of magnetic reconnection in the high- <jats:italic>β</jats:italic> plasma environment of the HCS, its interplay with the turbulent cascade, and the role of the mirror mode instability. </jats
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Journal articleSmith JR, Grobler C, Hodgson PJ, et al., 2026,
The climate opportunities and risks of contrail avoidance
, Nature Communications<jats:title>Abstract</jats:title> <jats:p> Navigational contrail avoidance presents an opportunity for rapid reduction in aviation-attributable warming. Here, we use the Aviation Climate and Air Quality Impacts model to evaluate the global temperature changes associated with contrail avoidance towards 2050. If no avoidance is adopted, aviation is projected to contribute 0.040 K of CO <jats:sub>2</jats:sub> warming and 0.054 K of contrail warming by 2050. The combined warming from aviation CO <jats:sub>2</jats:sub> and contrails is 19% of the difference between current temperatures and the +2 °C limit above pre-Industrial levels, i.e. 19% of our remaining temperature budget. An avoidance strategy phased in over 2035-2045 may recover 9% of this budget, but a 10-year delay may reduce this to 2%. The warming due to additional CO <jats:sub>2</jats:sub> emitted during avoidance is two orders of magnitude lower than the expected contrail warming reduction. For every year of delay, the world will be on average 0.003 K hotter in 2050. The most significant climate risk associated with contrail avoidance is therefore inaction. </jats:p>
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Journal articleXu H, Wang H, Prentice IC, et al., 2026,
Global variation in the ratio of sapwood to leaf area explained by optimality principles
, New Phytologist, ISSN: 0028-646X• The sapwood area supporting a given leaf area (Huber value, vH) reflects the coupling between carbon uptake and water transport and loss at a whole-plant level. Geographic variation in vH presumably reflect plant strategic adaptations but the lack of a general explanation for such variation hinders its representation in vegetation models and assessment of how its impact on the global carbon and water cycles. • Here we develop a simple hydraulic trait model to predict optimal vH by matching stem water supply and leaf water loss, and test its performance against two extensive plant hydraulic datasets. • We show that our eco-evolutionary optimality-based model explains nearly 60% of global vH variation in response to light, vapour pressure deficit, temperature and sapwood conductivity. Enhanced hydraulic efficiency with warmer temperatures reduces the sapwood area required to support a given leaf area, whereas high irradiance (supporting increased photosynthetic capacity) and drier air increase it. • This study thus provides a route to modelling variation in functional traits through the coordination of carbon uptake and water transport processes.
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Journal articleBrindley H, Di Natale G, Murray J, 2026,
Achieving consistency between in-situ and remotely sensed optical and microphysical properties of Arctic cirrus: the impact of far-infrared radiances
, Atmospheric Chemistry and Physics (ACP), ISSN: 1680-7316 -
Journal articleHassan A, Prentice IC, Liang X, 2026,
Insights into evapotranspiration partitioning based on hydrological observations using the generalized proportionality hypothesis
, Hydrology and Earth System Sciences, Vol: 30, Pages: 317-341<jats:p>Abstract. Evapotranspiration comprises transpiration, soil evaporation, and interception. The partitioning of evapotranspiration is challenging due to the lack of direct measurements and uncertainty of existing evapotranspiration partitioning methods. We propose a novel method to estimate long-term mean transpiration to evapotranspiration (Et/E) ratios based on the generalized proportionality hypothesis using long-term mean hydrological observations at the watershed scale. We tested the method using 648 watersheds in the United States classified into six vegetation types. We mitigated impacts of the variability associated with different Ep data products by rescaling their original Ep values using the product E/Ep ratios in combination with the observed E calculated from watershed water balance. With Ep thus rescaled, our method produced consistent Et/E across six widely used Ep products. Shrubs (0.33) and grasslands (0.32) showed lower mean Et/E than croplands (0.48) and forests (respectively 0.69, 0.60, and 0.70 for evergreen needleleaf, deciduous broadleaf, and mixed forests). Et/E showed significant dependence on aridity, leaf area index, and other hydrological and environmental conditions. Using Et/E estimates, we calculated transpiration to precipitation ratios (Et/P) ratios and revealed a bell-shaped curve at the watershed scale, which conformed to the bell-shaped relationship with the aridity index (AI) observed at the field and remote-sensing scales (Good et al., 2017). This relationship peaked at an Et/P between 0.5 and 0.6, corresponding to an AI between 2 and 3 depending on the Ep dataset used. These results strengthen our understanding of the interactions between plants and water and provide a new perspective on a long-standing challenge for hydrology and ecosystem science.</jats:p>
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Journal articleXu H, Rehkamper M, Jia Z, et al., 2026,
Anthropogenic emissions of volatile Cd detected in western tropical North Atlantic surface seawater
, Communications Earth & Environment, ISSN: 2662-4435The Cd concentrations and isotope compositions of open ocean surface waters are generally thought to be governed by internal cycling, and particularly by the balance between upwelling of more Cd-rich deeper water masses and Cd uptake by phytoplankton. Here we present a new dataset of coupled Cd isotope compositions and concentrations for seawater depth profiles sampled in the western tropical Atlantic Ocean during Leg 2 of the GEOTRACES GA02 section. A box model for the Cd source and sink fluxes of the oligotrophic surface waters of the study area shows that the observed light Cd isotope compositions and low Cd concentrations are a consequence of biological Cd uptake and atmospheric deposition of isotopically light anthropogenic Cd. Aerosols enriched in anthropogenic Cd thereby contributed at least 19%, and possibly more than 45%, to the dissolved surface water Cd inventory during the sampling period. This reveals that anthropogenic emissions of volatile Cd can have a key impact on the distribution of Cd in open ocean surface waters.
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Journal articleBucyibaruta G, Pirani M, Mitsakou C, et al., 2026,
Two-stage Bayesian factor analysis for air pollution source apportionment and health risk assessment
, Journal of Applied Statistics: Environmental Statistics and Data Science, ISSN: 2998-4696Air pollution, especially particulate matter (PM), presents significant public health challenges and is associated with several Sustainable Development Goals (SDGs), notably SDG 3 (Good Health and Well-being) and SDG 11 (Sustainable Cities and Communities). Effective policy development requires robust statistical approaches to identify pollution sources and quantify their health impacts with appropriate uncertainty. This study develops a novel two-stage Bayesian framework for air pollution source apportionment and health risk assessment, with the aim of quantifying the contribution of distinct particle sources to respiratory health outcomes in children, using particle number size distribution (PNSD) data from London. In the first stage, we construct a Bayesian dynamic factor model with autoregressive components to infer latent pollution sources, incorporating non-negativity constraints and accounting for temporal dependence. In the second stage, we assess the relationship between source-specific exposures and respiratory hospital admissions in children via a Poisson regression model, explicitly propagating uncertainty from the source apportionment stage to the health model. The model identifies four main sources: nucleation, traffic, urban activities, and secondary aerosols. Among these, traffic and secondary sources exhibit the strongest and most consistent associations with increased respiratory hospital admissions. Importantly, models that do not accountfor uncertainty propagation tend to overestimate health risk associations, underscoring the value of the proposed Bayesian framework. This work illustrates the advantages of integrating Bayesian methods for source apportionment and health effect estimation, with formal uncertainty propagation across model stages. The proposed framework enhances interpretability and supports evidence-based public health and environmental policy. It is readily extensible to other pollutants and settings, contributing to improved air
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Journal articleDai AZ, Gregory J, Ceppi P, 2026,
Understanding the Climate Response to Different Vertical Patterns of Radiative Forcing
, Geophysical Research Letters, Vol: 53, ISSN: 0094-8276The dependence of climate response on the vertical structure of radiative forcing is studied using a set of idealized experiments, with horizontally uniform and vertically confined forcings. We find for a given effective forcing magnitude, higher-altitude forcing causes a smaller global warming, owing to more negative cloud feedback. We present novel evidence relating this altitude dependence to sea-surface temperature patterns and tropospheric static stability. The imposed instantaneous forcings are horizontally uniform, but higher-altitude forcings more effectively suppress convection in the tropical warm pool, producing a more positive effective (adjusted) surface forcing in that region. This gives rise, during the subsequent climate change, to greater warming contrast between the warm pool and rest of the globe, and hence to increase in low cloud amount. Our results show that to achieve accurate climate projections under anthropogenic forcings, it is important to correctly represent the vertical structures of the applied radiative forcing.
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