Pressures on water resources are fueling conflicts between sectors. This trend will likely worsen under future climate-induced water stress, jeopardizing food, energy and human water security in most arid and semi-arid regions. Probabilistic analysis using stochastic optimization modeling can characterize multi-sector vulnerabilities and risks associated with future water stress. This study identifies the probabilistic trade-offs between agricultural, urban and energy sectors in the Ebro Basin (Spain). Two intervention policies have been examined and compared: (i) agricultural priority, and (ii) energy priority, for two planning horizons 2040-2070 and 2070-2100. Results show that the human water security goal is achieved under both intervention policies. However, the achievement of the food and energy security goals depends on the policy objectives and on the spatial location of irrigation schemes and hydropower plants, which result in different stream flows across the basin. The policy choice results in substantially different benefit gains and losses by sector and therefore by location. None of the sectoral production priority policy provides an equitable sharing of benefits among all sectors and locations under climate change, which is an important issue, because the success or failure of policy interventions would depend on the distribution of the gains and losses of benefits across the basin. Policy uptake by stakeholders would depend on reaching win-win outcomes where losers are compensated, while delivering acceptable levels of food, energy and human water security in large river basins. Information on the probabilistic trade-offs contributes to design water management strategies capable of addressing the multi-sector vulnerability.

Satellite altimetry has successfully monitored inland waters for more than 30 years and is increasingly important as the demand for freshwater grows and climate change accelerates. Launched in December 2022, the Surface Water and Ocean Topography (SWOT) satellite is the first to provide 2D spatially distributed elevation measurements, with a nominal 21-day revisit time and better coverage depending on latitude. Here, we evaluate the SWOT L2 HR PIXC 2.0 data product for constructing water surface elevation (WSE) time series at 40 Danish lakes with a surface area above 0.25km2 via the summary measures RMSE and Pearson Correlation Coefficient (PCC). Two methods to derive the bias between the SWOT-based WSE and the gauge water level were tested; a constant bias and a newly proposed acquisition-specific bias. Based on the 40 gauged lakes we find a median RMSE of 5.76cm and 8.87cm and PCC of 0.93 and 0.76, for the acquisition-specific bias and constant bias, respectively.   Additionally, we examined the spatial variations of the water surface elevations in the L2 HR PIXC 2.0 data product. Compared with ICESat-2, we found that the spatially distributed variations in SWOT data were unlikely to represent real physical phenomena. Our findings highlight the potential of SWOT for generating high-accuracy WSE time series, for small lakes. SWOT’s broad spatial coverage offers far greater temporal frequency (for Danish lakes: usually 3 to 4 acquisitions per 21-day orbit) compared to traditional satellite altimeters, enabling new insights into water level dynamics that were previously unattainable.

Topobathymetric scanning LiDAR deployed on unmanned aerial systems (UAS) is a powerful tool for high-resolution mapping of the dynamic interface between topography and bathymetry. However, standardized methods for empirical resolution validation have not been widely adopted across LiDAR applications. While theoretical models of idealized LiDAR sampling resolution can be used to describe topographical resolution, misrepresented or unknown behaviors in an instrument, platform, or environment can degrade expected performance or introduce georeferencing inaccuracies. Furthermore, bathymetric resolution is strongly dependent on water surface and column conditions. Thus, only empirical methods for evaluating resolution will provide reliable estimates for both topographic and bathymetric surveys. Presented is an extension of standard modulation transfer function (MTF) methods used by passive imaging systems applied to high-resolution scanning LiDAR. Compact retroreflectors characterized as point and line sources are employed to empirically assess effective LiDAR system resolution through MTF analysis in topographic and bathymetric scenes. These targets enable MTF analyses using range-height measurements without reliance on intensity data, promoting widespread applicability among LiDAR systems. Empirical MTFs calculated using these targets are compared against theory-derived counterparts as empirical measurements elucidate influences by elements that are unknown or difficult to model. Simulated point cloud data were incorporated into theoretical MTF descriptions to better represent empirically-derived topographic MTFs, revealing mirror pointing uncertainties in the across-track axis. Similarly, theoretical bathymetric MTFs augmented with simulated, subaqueous data enabled water surface slope estimation using empirical measurements of submerged retroreflector targets, where rough water surfaces strongly influenced beam steering and the corresponding point spread MTFs.

Based on new zircon and apatite (U-Th-Sm)/He and 40Ar/39Ar ages, along with published thermochronometric data, we derive first-order constraints on the tectonic and thermal evolution of the Dent Blanche Tectonic System (DBTS), an Austroalpine nappe in the Western Alps underlain by former Ligure-Piemontese oceanic units. Overall, ZHe ages are approximately 30 Ma, and most AHe ages are younger, ranging from ~20 to ~12 Ma, with exceptionally young ages (~2.5 Ma) from a sample collected at a lower elevation in the Valpelline Valley. MAr ages are scattered, spanning from ~250 Ma to ~29 Ma, and many micas are affected by excess radiogenic 40Ar *. Inverse thermal modeling of the cooling ages, constrained with the younger MAr ages from the same samples, indicates that DBTS experienced rapid cooling associated with the Alpine orogeny during the Eocene-Oligocene. Since then, cooling has slowed one to two-fold compared to adjacent units to the north. The Pliocene-Pleistocene AHe ages from the Valpelline Valley were reset and experienced rapid cooling starting around ~2.5 Ma. This increase in cooling is interpreted as the localized effect of glacial erosion, which steepened tributary valleys adjoining the Aosta Valley, as indicated by the analysis of normalized fluvial channel steepness (Ksn). This is consistent with similar increased denudation rates since the Pliocene, as reported in the Rhone Valley and Mont Blanche area of the Western Alps.

The directional derivative approach (DDA) has the potential to rapidly and accurately quantify emission distributions based on the directional derivative of satellite-observed column amounts with respect to the horizontal wind. From the first principles, this paper derives the DDA emission estimators with a range of complexity by vertically integrating the 3D continuity equation and simplifying the results under several assumptions and approximations. The connection and difference between the DDA and a widely used divergence method for emission estimation are highlighted. A key difference is that the DDA integrates from the surface to an intermediate altitude instead of to the top of the observed column. This leads to the inherent background removal of the DDA, in contrast to the explicit background removal necessitated by the divergence method theory. Linear fittings are used to account for the effects of topography, chemical reactions, and retrieval biases. Realistic estimators of NOx emissions using satellite-observed NO2 column amounts are proposed, leveraging external climatology of the NOx:NO2 ratio and its directional derivative. These estimators are evaluated within a WRF-CMAQ simulation of NOx by comparisons with the model NOx emissions. The DDA estimators consistently outperform the divergence method estimator, and the DDA estimator that considers both topography and chemistry features the lowest root mean square error (RMSE). Lessons learned from this study using synthetic model data can be readily applied to the usage of actual satellite observations for emission estimation.

Magnetic field-line curvature scattering (FLCS) of energetic particles in the equatorial magnetotail results in isotropization of pitch-angle distributions, loss-cone filling, and precipitation above a minimum energy at a given latitude. At a fixed energy, the lowest latitude of isotropization is the isotropy boundary (IB) for that energy. Nominally, the IB (latitude) exhibits a characteristic energy dependence due to the monotonic variation of the equatorial magnetic field intensity Beq with radial distance. Deviations from this nominal IB dispersion can occur if the radial Beq variation (spatial or temporal) is non-mononotic and/or if other precipitation mechanisms prevail. With its sensitive and detailed measurements of electron spectra up to relativistic energies, ELFIN’s recent observations reveal a variety of electron IBe patterns near magnetic midnight which are repeatable enough to warrant classification. This study aims to categorize the various IBe patterns observed by ELFIN’s high-fidelity but short lived dataset (a few months), compare them with simultaneous nearby POES observations, which are made with a limited energy coverage and resolution but last for decades, and discuss their possible interpretation. The general agreement between ELFIN and POES IB observations indicate a relatively large-scale nature of IBe patterns. Surprisingly, there exists a large number (up to 2/3 of all events) of non-monotonic-or steep/multiple-IB patterns. This suggest an abundance of non-trivial tail current sheet structures or a mixed contribution of two mechanisms in the vicinity of IBe in these cases.

Agricultural cooperatives (co-ops) are increasingly recognised for their capacity to enhance resilience in the face of crises such as climate change, economic disruptions, and pandemics. This study investigates how governance structures and adaptive project management strategies contribute to effective crisis management in coops. Initial findings reveal that regulatory compliance acts as both a constraint and an enabler, while economic volatility drives the need for costly technological investments. External stakeholder influence provides essential resources but imposes governance to align internal and external priorities. Social capital, manifesting as community trust and collaboration, supports crisis response but can be weakened under financial stress. Hybrid governance frameworks emerge as vital, balancing member engagement with professional oversight to maintain organisational stability. We propose the Crisis Resilience in Agricultural Cooperatives conceptual framework, which links external pressures, internal dynamics, and resource availability to resilience outcomes. This research highlights the importance of strategic governance, adaptive project management, and effective social networks in fostering coop resilience and provides guidance for policymakers and practitioners.

Estuaries in the northern California current system (NCCS) experience seasonally reversing wind stress which is expected to impact the origin and properties of inflowing ocean water. Wind stress has been shown to affect the source of estuarine inflow by driving alongshelf currents. However, the effects of vertical transport by wind-driven Ekman dynamics and other shelf and slope currents on inflow have yet to be explored. Variations in inflow to two NCCS estuarine systems, the Salish Sea and the Columbia River estuary, were studied using particle tracking in a hydrodynamic model. Particles were released in a grid extending two degrees of latitude north and south of each estuary every two weeks of 2017 and tracked for sixty days. Inflow was identified as particles that crossed the estuary mouths. Wind stress was compared with initial horizontal and vertical positions and physical properties of shelf inflow particles. Inflow to the Salish Sea came from Vancouver Island and Washington slope water upwelled through canyons during upwelling-favorable wind stress, and from Washington slope water or Columbia River plume water during downwelling-favorable wind stress. Inflow to the Columbia River estuary came from Washington shelf bottom water during upwelling-favorable wind stress and Oregon shelf surface water during downwelling-favorable wind stress. For both estuaries, upwelling-favorable wind stress direction was significantly correlated with a denser and deeper shelf inflow source north of the estuary mouth. These results may help predict the source and properties of inflow to estuaries in other regions with known wind or shelf current patterns.

Implicit time-stepping for advection is applied locally in space and time where Courant numbers are large, but standard explicit time-stepping is used for the remaining solution which is typically the majority. This adaptively implicit advection scheme facilitates efficient and robust integrations with long time-steps while having negligible impact on the overall accuracy, and achieving monotonicity and local conservation on general meshes. A novel and important aspect for the efficiency of the approach is that only one linear solver iteration is needed for each advection solve. The implementation in this paper uses a second-order Runge-Kutta implicit/explicit time-stepping in combination with a second/third-order finite volume spatial discretisation. We demonstrate the adaptively implicit advection in the context of deformational flow advection on the sphere and a fully compressible model for atmospheric flows. Tracers are advected over the poles of latitude-longitude grids with very large Courant numbers and through hexagonal and cubed-sphere meshes with the same algorithm. Buoyant flow simulations with strong local updrafts also benefit from adaptively implicit advection. Stably stratified flow simulations require a stable combination of implicit treatment of gravity and acoustic waves as well as advection in order to achieve long stable time-steps.

A document by Frederic Allegrini. Click on the document to view its contents.

The process of two-phase fluid displacement in the porous medium is still poorly understood partly due to the absence of effective reconstruction methods featured in a 3D real-time fashion. This manuscript proposes the application of thermoacoustics (TA) imaging, an emerging real-time imaging technique, to reconstruct the dynamic surfactant-enhanced imbibition process into the oil-saturated sand. It is both theoretically and experimentally demonstrated that a significant TA contrast exists between the water-saturated sand and oil-saturated sand under the same microwave power. In the experiment, a U-shaped infiltration path is embedded 20mm underneath the oil-saturated sand as the ground truth profile of the water flow. A calibration process is conducted to account for the amplitude attenuation and velocity dispersion effects of the TA wave in the sand, and a two-layered medium sensing matrix is built for the inversion process. The reconstructed images match well with the infiltration path, which makes it feasible to monitor the subsurface 3D water-oil displacement in non-transparent porous sand in a real-time fashion.

This report highlights the complex interplay between cardiac func8on, metabolic disorders, and the impact of Oshtoran Syndrome on overall health. Par8cular emphasis is placed on the implica8ons of a le? ventricular ejec8on frac8on (LV-EF) decline, PDH cytopathy, and the resultant metabolic dysregula8on. Addi8onally, the cri8cal role of catecholamine suppression in preven8ng poten8ally life-threatening episodes is discussed. Introduc/on: Oshtoran Syndrome (H63D Syndrome Type-3) presents a mul8faceted clinical challenge, characterized by both cardiac and metabolic complica8ons. This report examines the deteriora8on in cardiac func8on, the metabolic impact of PDH cytopathy, and the systemic effects observed in a pa8ent with this syndrome, along with the essen8al role of catecholamine suppression. 1,4,5 Cardiac issues: Le? Ventricular Ejec8on Frac8on (LV-EF): The pa8ent's LV-EF has decreased from 63% to 49%, indica8ng a significant impairment in the heart's ability to pump blood and oxygen efficiently. This decline reflects a compromised cardiac func8on, likely contribu8ng to systemic hypoperfusion and metabolic stress. 9,10,11,12

Sudden Stratospheric Warmings (SSW) and Elevated Stratopause (ES) events are mid-to-high latitudinal, atmospheric wave-driven phenomena leading to significant changes in wind, temperatures, and vertical mass transport, especially in stratospheric and mesospheric altitudes. Presumably, SSW and ES-induced changes also cause modifications in the highly variable D-region ionization. This bottom side of the ionosphere behaves with the Earth’s surface as a reflection boundary for Very Low Frequency (VLF) radio signal transmission used for long-distance communication. Since perturbations of the D-region ionization are also notable in the VLF signal, it is a valuable tool for continuous investigations of the D-region. Here, we study the impact of four SSW/ES events on the VLF signal amplitude between the high latitude transmitter-receiver link Keflavik, Iceland, to NyÅlesund, Svalbard, to gain further knowledge about interactions between the D-region and the atmosphere during these atmospheric phenomena. For three of four SSW/ES events, a very similar VLF signal amplitude signature is observed, characterized by a significant increase during the SSW period in the signal amplitude followed by a decrease during the ES period. This study aims to reveal a possible mechanism driving these similar VLF signal amplitude variations, involving modified electron neutral collision frequencies and electron densities due to changed temperatures and minor constituent concentrations according to the SSW/ES events. However, the VLF signal amplitude for one event increased two weeks later than during the other three events and did not show a decrease during the ES period. Possible causes for the different VLF signal amplitude variations are discussed.

The shared tectonic history of southwestern Australia and East Antarctica facilitates the exchange of geological insights between the regions. In this study, we present coupled susceptibility and density models obtained through the joint inversion of magnetic and gravity data. By assuming a common geological source for both signals, our coupling method minimizes misfits and variation in information, thereby enhancing the correlation between susceptibility and density. The resulting anomalies demonstrate structural continuity between the continents, aligning closely with major shear zones and seismic reflectors. Combining these results with machine learning, geochemical, and petrophysical databases, we predict a high-resolution ($10$ km) heat production map for East Antarctica. Utilizing a Markov Chain Monte Carlo (MCMC) algorithm, we further develop a geothermal heat flow map with greater spatial variability than previous studies, yielding an average of $55\,$mW/m$^2$ in East Antarctica and $46\,$mW/m$^2$ in southwestern Australia. Our results provide a crucial high-resolution boundary condition for ice sheet simulations, enabling more realistic estimates of basal meltwater production and ice temperatures.

Recent observations from the ExoMars Trace Gas Orbiter (TGO) have revealed the presence of hydrogen chloride (HCl) in the martian atmosphere. HCl shows strong seasonality, primarily appearing during Mars’ perihelion period and rapidly decreasing afterwards faster than projected from photolysis and gas-phase chemistry. HCl also shows anti-correlation with atmospheric water ice. One candidate explanation is heterogeneous chemistry. We present the first results from a heterogeneous chlorine chemistry scheme incorporated into a Mars global climate model (GCM), with atmospheric dust/water ice parameterized as an HCl source/sink respectively. Results were compared against a Mars GCM with gas-phase only chlorine chemistry and observations from TGO’s Atmospheric Chemistry Suite (ACS). We found that the heterogeneous scheme significantly improved the modelled HCl seasonal, latitudinal, and vertical distribution, supporting a crucial role for heterogeneous chemistry in Mars’ chlorine cycle. Remaining discrepancies show that further work is needed to characterise the exact aerosol reactions involved.

Weather stations can represent local weather variability and extremes more reliably than gridded products and are therefore better suited for local climate impact applications like calculation of the Fire Weather Index (FWI), a multivariate index for wildfire danger assessment. However, the prediction at multiple sites poses the challenge of preserving spatial consistency across locations, requiring a suitable multi-site approach. This study evaluates the potential of Convolutional Neural Networks (CNNs) for statistical downscaling (SD) of FWI predictions across the Iberian Peninsula. We compare our CNN-Multi-Gaussian (CNN-MG) model against Generalized Linear Models (GLMs) and a benchmark single-site CNN approach. Our evaluation focuses on predictive accuracy, distributional congruence, spatial coherence and extreme events reproducibility using daily FWI data from 29 locations in Spain. The CNN-MG model, which integrates the covariance structure of the predictands, outperformed other methods in representing FWI distributions across both single and multisite scales. Moreover, our model provides greater physical interpretability via eXplainable Artificial Intelligence (XAI) techniques, while also emphasizing simplicity and ease of training.

A document by Thomas "TIM" Harris. Click on the document to view its contents.

The ”Relámpago del Catatumbo” is a unique phenomenon that occurs over Lake Maracaibo, where the most intense lightning activity on the planet takes place. In this work, we extend the study of lightning activity in Lake Maracaibo and its surroundings by a decade, evaluating the period from 2014 to 2023. The results show that the hourly distributions of lightning activity are correlated with the variations of deep convective events in the region; while, the seasonal variations in lightning strikes are correlated with the monthly variations in the mean water temperature of Lake Maracaibo. These findings suggest that the Lake may be providing the necessary water vapor for the development of storm systems that form in the region. It was found that the diurnal and monthly variations of the lightning activity have not changed substantially over the years, as these variations are, with a high degree of significance, very similar to those found in the period 2005-2010 by Bürgesser et al. (2012). The analysis of the interannual variations in lightning strikes for the period does not show any indication of a systematic increase or decrease in lightning activity; however, it can be noted that there is an increase in lightning activity in the last two years analyzed, 2022 and 2023.