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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 articleWarder SC, Piggott MD, 2026,
Wind farm wake losses under future build-out scenarios
, Wind Energy and Engineering Research, Vol: 5, Pages: 100025-100025, ISSN: 2950-3604 -
Journal articleShu S, Yang X, Ming Z, et al., 2026,
A carbon reduction incentive model for crowdsourced urban freight: Facilitating freight pooling and electric truck adoption
, Transportation Research Part E Logistics and Transportation Review, Vol: 209, ISSN: 1366-5545Urban freight transport faces significant decarbonization pressure, yet existing strategies such as freight pooling and electric truck adoption often struggle with limited uptake due to operational complexities, costs, and infrastructure challenges. Critically, current research lacks an integrated, operational incentive framework specifically designed for multi-stakeholder participation in urban crowdsourced logistics, where task-level operational decisions across multiple stakeholders play a central role in system-level carbon reduction. This study introduces a Carbon Reduction Incentive Model (CRIM) that addresses this gap. The CRIM incentivizes individual shippers and independent carriers within a crowdsourced logistics system by assigning task-level rewards for freight pooling and electric truck usage. Rewards are quantified by tonne-kilometer savings relative to conventional individual diesel deliveries, further adjusted by a time-based factor to encourage off-peak operations. The CRIM is embedded within an enhanced pick-up and delivery model that explicitly accounts for stakeholder cost components, vehicle heterogeneity, charging requirements, and time-sensitive feasibility (PDPTW-HEC). To optimize the system’s complex trade-off between costs and carbon emissions, a customized heuristic algorithm is developed. Scenario-based case studies using real-world data and international carbon accounting standards validate the proposed incentive model’s performance. Results demonstrate that CRIM can achieve 9.5–38.1% higher electric truck adoption and an 8.4–28.7% reduction in total carbon emissions. This framework offers a practical and scalable approach for designing and evaluating task-level carbon reduction incentives in urban freight operations.
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Journal articleStewart JA, Robinson LF, Rae JWB, et al., 2026,
Accumulation of remineralised carbon and nutrients in the mid-depth Atlantic during Heinrich Stadial 1 and the Younger Dryas
, Earth and Planetary Science Letters, Vol: 679, ISSN: 0012-821XAtmospheric CO<inf>2</inf> and the temperature of the interior Atlantic Ocean both increased in 2-steps during the last deglaciation, particularly during Heinrich Stadial 1 (HS1; ∼16 ka) and the Younger Dryas (YD; ∼12 ka). However, what drove these punctuated rises remains a long-standing question. The role of deep-ocean carbon storage, release, and redistribution continues to be debated. To establish the role of ocean circulation in deglacial carbon and nutrient cycling, we present new multi-proxy data in sub-fossil corals from mid-depths in the Equatorial Atlantic, including boron isotopes (δ<sup>11</sup>B; seawater pH), Ba/Ca (seawater [Ba] and refractory nutrients), and neodymium isotopes (ε<inf>Nd</inf>; provenance of seawater signal). Corals are dated to a precise radiometric age scale and combined with previously published radiocarbon and temperature proxy measurements on the same samples. Our data reveal abrupt intervals (∼500 years) of notably low pH, Ba-rich, and radiocarbon-depleted (old) waters at 15.4 and 12.0 ka during HS1 and the YD at depths of ∼1700 m. However, very low ε<inf>Nd</inf> (unradiogenic) values suggest that these corals were bathed in northern-sourced Atlantic waters throughout the deglaciation. These results imply that these (old) carbon- and nutrient-rich intermediate waters were not sourced from the carbon- and nutrient-rich Southern Ocean via Antarctic Intermediate Water (AAIW). Instead, carbon and nutrient accumulation at mid-depths in the tropical Atlantic was likely the result of remineralisation of organic matter at times of Atlantic Meridional Overturning Circulation (AMOC) slowdown. The Atlantic Ocean interior was therefore accumulating heat and carbon during these times when deepwater flushing was minimal, thus acting to partially dampen atmospheric CO<inf>2</inf> rise and warming caused by ventilation of the Southern and Pacific
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Journal articleMillar O, Ma L, Karmpadakis I, 2026,
Experimental assessment and prediction of wave loading around abrupt depth transitions
, Coastal Engineering, Vol: 206, Pages: 104969-104969, ISSN: 0378-3839 -
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 articleWilson Kemsley S, Nowack P, Ceppi P, 2026,
Recent Cloud Controlling Factor Analyses Indicate Higher Climate Sensitivity
, Geophysical Research Letters, Vol: 53, ISSN: 0094-8276Cloud feedback is a dominant source of uncertainty in climate model estimates of equilibrium climate sensitivity (ECS). Cloud controlling factor analysis can observationally constrain cloud feedback. For the first time, we use separate rather than unified frameworks to assess high- and low-cloud feedbacks and constrain the net cloud feedback and subsequently, the ECS. We find a robustly positive cloud feedback (i.e., a negative feedback is (Formula presented.) % probable), indicating that clouds amplify global warming. We assess the individual and combined impacts of our cloud feedback constraints on ECS using three approaches. Two indicate an upward ECS shift with reduced uncertainty, preserving ECS–feedback correlations but using cloud feedback as a single line of evidence. The third, a Bayesian framework combining multiple lines of evidence, also suggests a higher ECS but with a smaller increase and broader confidence range.
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Journal articleMcCain K, Vicco A, Morgenstern C, et al., 2026,
A systematic review and meta-analysis of Zika virus epidemiology
, Nature Health, ISSN: 3005-0693Zika virus (ZIKV), classified as a priority pathogen by the World Health Organization, is an Aedes-borne arbovirus that can cause neurological complications and birth defects in newborns of mothers infected during pregnancy. We conducted a systematic review of peer-reviewed studies reporting ZIKV epidemiological parameters, transmission models and outbreaks (PROSPERO CRD42023393345) to characterize its transmissibility, seroprevalence, risk factors, disease sequelae and natural history. We performed meta-analyses of the proportions of congenital Zika syndrome, pregnancy loss among ZIKV-infected mothers and symptomatic cases. We extracted information from 574 studies. Across 418 included studies assigned a high-quality score, we extracted 969 parameters, 127 outbreak records and 154 models. Using random-effects models, we estimated proportions of congenital Zika syndrome (4.65%, 95% confidence interval (CI): 3.38–6.67%), pregnancy loss (2.48%, 95% CI: 1.62–3.78%) and symptomatic cases (51.20%, 95% CI: 38.00–64.23%). Seroprevalence estimates (n = 354) were retrieved beyond South America and French Polynesia. Basic reproduction number estimates (n = 77) ranged between 1.12 and 7.4. We found 66 human epidemiological delay estimates, including the intrinsic incubation period (n = 11, range: 4–12.1 days), infectious period (n = 15, range: 3–50 days), extrinsic incubation period (n = 22, range: 5.1–24.2 days) and serial interval (n = 27, range: 7.4–32.9 days). These data are available in the R package ‘epireview’ (version 1.4.5). We provide a comprehensive systematic summary of ZIKV epidemiology, revealing large heterogeneities and inconsistencies in the reporting of parameter estimates, study designs and parameter definitions and underscoring the need for standardized epidemiological definitions.
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Journal articleLau KH, Toumi R, 2026,
Does vertical wind shear increase tropical cyclone rain?
, Quarterly Journal of the Royal Meteorological Society, ISSN: 0035-9009<jats:title>Abstract</jats:title> <jats:p>Changes in tropical cyclone (TC) rain induced by vertical wind shear (VWS) have significant implications. Using a 26‐year state‐of‐the‐art precipitation dataset, this study provides a systematic analysis of the responses of TC rain to VWS. Results reveal an unexpected VWS‐induced rain volume enhancement despite reduced TC intensity, with rain volume up to 23% higher in high‐ versus low‐shear conditions. The responses are spatially asymmetric: rainfall increases in the outer region but decreases in the inner core, and enhancements downshear generally outweigh suppressions upshear, yielding a net increase in rain production. Beyond the mean response, VWS also modifies rainfall extremes and storm structure. It reduces the maximum azimuthal mean rain rate, whereas the maximum local rain rate remains largely unchanged and even intensifies slightly in the strongest TCs. The radii of rainfall maxima expand outward with shear, and the peak local rain rate tends to converge with the azimuthal mean maximum at high shear. When adjusted by storm intensity, stronger shear enables higher rain rates, larger rain areas, and greater rain volumes for the same TC intensity. These results challenge the conventional view of shear as purely detrimental to TCs, revealing a dual role: VWS weakens winds but enhances rainfall, potentially mitigating wind damage while amplifying flood risk. This trade‐off underscores the need to account for shear‐induced hydrological impacts in TC hazard assessment and prediction.</jats:p>
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Journal articleRoss A, Ochoa-Tocachi B, Bonnesoeur V, et al., 2026,
Quantifying and regionalizing land use impacts on catchment response times with high-frequency observations
, Water Resources Research, ISSN: 0043-1397Land use and land cover change (LUCC) can affect the hydrological response time of rivers. However, it is difficult to generate robust and quantitative evidence of this impact at the catchment scale. This lack of evidence also affects the development of rainfall-runoff models to make ex-ante predictions. Here, we analyze high-frequency observational data from a network of pairwise catchments in the tropical Andes and find a statistically significant impact of intensive land use on the hydrological response time, which can be used for regionalization. First, we isolated individual rainfall response events from 5-minute precipitation and discharge time series of 16 catchments (8 pairs). We then fitted unit hydrographs on these events to estimate the catchment response times. These response times were subsequently regionalized by, first, applying a forward stepwise regression to select statistically significant catchment characteristics including land use and land cover, then, fitting a linear mixed-effects model with the selected characteristics to account for within-site variability between pairs. We find that catchments with intensive land use have a significantly quicker response than their natural counterparts. Differences were often sub-hourly, highlighting the value of high-frequency monitoring. Forward stepwise regression identified only catchment area and intensive land use percentage as statistically significant predictors. Model coefficients show that, even when considering other catchment characteristics, increasing intensive land use percentage decreases response times. This study provides solid evidence and a robust methodology to quantify the impacts of LUCC on catchment hydrology.
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