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Evapotranspiration (ET) plays a crucial role in the global water and energy cycle. Upscaling instantaneous ET ([Formula: see text]) to daily ET ([Formula: see text]) is vital for thermal-based ET estimation. Conventional methods – such as the constant evaporative fraction method (ConEF), radiation-based method, and evaporative ratio method – often overlook environmental factors, leading to biased estimates of [Formula: see text] from [Formula: see text]. To resolve this issue, this study aimed to assess four machine learning (ML) algorithms—XGBoost, LightGBM, AdaBoost, and Random Forest—to integrate meteorological and remote sensing data for upscaling [Formula: see text] across 88 global flux sites. Each ML model was tested with eight different variable combinations. Results indicated that XGBoost exhibited the best performance, with a root mean square error (RMSE) generally below 13 W [Formula: see text] in estimating [Formula: see text] from [Formula: see text]. The best variable combination simultaneously considers evaporative fraction, available energy, meteorology factors, remote sensing albedo, normalized vegetation index, and leaf area index. Using this combination, the XGBoost model achieved an [Formula: see text] = 0.88 and an RMSE = 12.33 W [Formula: see text], outperforming the ConEF method ([Formula: see text] = 0.71 and RMSE = 18.86 W [Formula: see text]) and its expansions. These findings support the application of ML models in ET upscaling, enabling ET estimation across large spatiotemporal scales.

Abstract This paper explores the response to Holocene ash inundation in different sub‐environments of two fluvio‐lacustrine systems, Las Piedritas and Totoral, focussing on the processes of volcaniclastic remobilisation. Sediment cores and outcrops were used to recognise three deposit types, noting how some differ from lahars, through sedimentological and stratigraphic analysis: (1) thick, laterally discontinuous, pumice‐dominated deposits occur overlying alluvial plain and lower terrace surfaces across both watersheds; (2) chaotic, extremely poorly sorted and matrix‐supported beds composed of both epiclastic and pyroclastic material occur as two conspicuous deposits at Las Piedritas outcrops, in a low‐gradient confined channel setting; and (3) layers with an exclusively pyroclastic composition and no flow sedimentary structures or fragment roundness were found draping each of the two chaotic intervals and intercalating with the background sediment in Las Piedritas prodelta. Thick pumice packages capping the floodplains resulted from the overflow of streams carrying a floating pumice load. Due to its positive buoyancy, the pumice is transported as a slowly moving overlying mantle without mixing with the streamflow. The disorganised pattern and poor sorting of the matrix‐rich polymictic beds are consistent with laminar, gravity‐driven, high‐concentration flows. They constitute secondary lahars, originating upstream from large run‐off processes that reworked a pyroclastic substrate. The lack of reworking features in the vitric‐rich units identified in the lake core retrieved from Las Piedritas prodelta, as well as the continuous and widespread occurrences of those interbedded in upstream outcrops, indicate an airfall origin. No reworked tephra unit is recognised in the prodelta sediment record, although various deposits from the hydrologic remobilisation of airfall tephra are found along the subaerial portion of both watersheds. Apparently, large amounts of flotation‐remobilised tephra were retained on the delta plain, while another considerable fraction would have been carried away from the creek mouth under the influence of dominant regional winds.

Abstract Planar lamination is a ubiquitous component of modern and ancient fine‐grained sediments deposited by subaqueous sediment gravity flows. These sediments commonly exhibit alternating sub‐millimetre‐thick, sharply bounded silt‐rich and clay‐rich layers that change little in thickness or sediment texture over lateral distances that range up to at least several tens of metres. Silt‐rich layers are moderately to well‐sorted and a few tens to hundreds of microns to a single silt‐grain thick. In contrast, clay‐rich layers are more poorly sorted, and a few tens to hundreds of microns thick. The thickness and regular alternation of these texturally differentiated interlayers, in addition to the absence of features suggesting transport bypass or deposition by migrating rugged bed forms, suggest alternating physical processes and related modes of deposition in the near‐bed region immediately above the bed. Previous interpretations have focussed on clay flocculation, which is difficult to reconcile with the high fluid shear conditions in the near‐bed region. Here it is suggested that in the millimetre to sub‐millimetre‐thick viscous sublayer at the base of a hydraulically smooth turbulent flow, a combination of high fluid shear and sediment concentration initially leads to shear thinning and enhanced mobility in the lower part of the flow, and for silt to continue settling to the bed forming a well‐sorted silt lamina. As silt settles and clay‐size sediment increases in concentration, hydrodynamic lubrication forces strengthen and reduce mobility of the near‐bed part of the flow. This condition is then perturbed by a bedward‐directed outer flow disturbance that dramatically increases frictional stresses and effective fluid viscosity and ultimately shear jamming that causes gelling and deposition of a poorly sorted clay‐rich layer. This process is then repeated multiple times to build up a deposit composed of alternating silt‐rich and clay‐rich laminae overlain by structureless mud deposited directly from suspension.

Abstract Jurassic and Palaeocene tidal deposits of the epeiric Western Interior Sea in Wyoming, USA, differ significantly due to their contrasting climates and tectonic, geographic and depositional settings. Tidally generated, cross‐bedded sandstone bodies contained by incisions are common to both settings and can potentially be uncritically attributed to marine flooding of fluvial systems. Key differences in lithology, ichnology and relationships with surrounding sediment reveal fundamentally different depositional settings, however. The Jurassic system occupied a low accommodation, semi‐arid environment, with geographically open shorelines as relative sea‐level fell, creating an unconformable contact with the underlying, storm wave‐dominated shelf and shoreface deposits. Siliciclastic, intertidal flats formed adjacent to coastal aeolian and fluvial environments during brief turnarounds from the degradational (forced regressive) to aggradational and retrogradational (transgressive) system tract. Basinward of these environments, metre to decimetre‐scale cross‐bedded, bioclastic, subtidal compound dunes and tidal inlet complexes accumulated in areas of minimal clastic flux and within incisions created by submarine tidal currents. By contrast, the Palaeocene tidal systems formed in a high accommodation, subtropical setting, as rising sea levels forced the fluvial to marine transition zone landward and flooded coastal swamps, forming geographically irregular, back‐barrier complexes and tidally influenced fluvial systems. High volumes of siliciclastics, terrigenous organic material and freshwater were delivered by the rivers and created physicochemical stress on the marine embayments. Sandy tidal flat deposits accumulated in lagoons and interdistributary bays, but unlike the Jurassic examples, they do not mark a turnaround from the falling stage to the transgressive system tract. The potential preservation window for tidalites is significantly greater vertically in the aggradational to retrogradational setting than in the degradational system due to greater accommodation. The preservation window is vertically smaller, but areally greater in the Jurassic, forced regressive system because of basinward enhancement of tidal currents driven by complex palaeobathymetry caused by tectonic activity of local pre‐Laramide uplifts.

Abstract Deltas are deposits directly accumulated by land‐generated gravity flows in a standing body of water. The paradigm of deltaic sedimentation has dramatically changed during recent years, from the popular very simplified ternary models of marine littoral deltas towards more realistic and comprehensive models, considering the importance of sediment‐laden river discharges. Ternary delta models were designed for clean rivers, where a stream flow drags the sediments. Depending on the basin dynamics, these littoral deposits can be modified, forming tidal‐dominated, wave‐dominated or fluvial‐dominated littoral deltas. In recent years, a new classification of delta systems was proposed, based on contrasting the salinity of the receiving water body with the bulk density of the incoming fluvial discharge. Rivers are highly dynamic systems, and their discharges can be very variable in terms of flow duration and sediment concentration. Additionally, the salinity of the receiving water body can exhibit significant variability, especially in closed lakes and epicontinental seas, ranging from freshwater to brines. This scenario allows the distinction of three major delta categories (hypopycnal, homopycnal and hyperpycnal deltas) which can be in turn subdivided, defining seven delta types. Hypopycnal deltas form when the bulk density of the incoming flow is lower than the density of the water in the basin, allowing the definition of three delta types, corresponding to hypersaline littoral deltas, marine littoral deltas and brackish littoral deltas. Homopycnal deltas form when the bulk density of the incoming flow is similar to the density of the water in the basin, defining a delta type termed homopycnal littoral deltas. Hyperpycnal deltas form when the bulk density of the incoming flow is higher than the density of the water in the basin, allowing the definition of three categories termed hyperpycnal littoral deltas, hyperpycnal subaqueous deltas and hyperpycnal fan deltas.

Abstract Mass movements are common on the continental slope, affecting not only the subsequent sea floor morphology but often substantially modifying the underlying deposits. Various styles of substrate interaction have been recognised, representing the various degrees of involvement of the underlying material and its incorporation into the mass movement. This work presents a new style of basal interaction not previously described. Based on the morphology of the basal surface of a mass transport deposit, this can be recognised both in seismic data and in an outcrop analogue. A subsurface example, from an ca 100 m thick mass transport deposit located in Santos Basin, offshore Brazil, displays a basal surface with spoon‐shaped scours or scoops. These scoops are of the order of tens up to 400 m in maximum dimension, where masses of underlying sediment have been removed and incorporated into the mass movement. Outcrops used for this work are located in La Rioja Province, Western Argentina, where the study involves a well‐exposed ca 200 m thick mass transport deposit that crops out continuously over 7 km. Its basal surface is incised irregularly into the underlying sandstones, incorporating the blocks of sandstone into the mass movement. The striking similarities observed between outcrop examples and the northern Santos Basin suggest that they can be effective analogues, facilitating a comprehensive understanding of mass transport deposit dynamics across diverse basin environments.

Abstract The French Flemish Coastal Plain, which extends from Denmark to France, is characterised by a topography close to sea level and protected by a system of coastal dunes. Quaternary sediments, comprised of marine, estuarine and continental deposits, accumulated by infilling and then prograding above a network of incised valleys. This study focusses on the Holocene infill of the Denna palaeoestuary, south‐west to Dunkerque. Surface geophysics (electrical conductivity and ground‐penetrating radar) and vibrocore data are used to reconstruct the landscape evolution during the last stages of sedimentation. The conductivity map highlights the last network of tidal channels, ditches and dikes of the eastern side of the palaeoestuary. Over the upper 4 m of the infill, the ground‐penetrating radar profiles show two superimposed units. The bottom unit is composed of meandering channel bars and the top unit of flat strata intersected by sparse channels, mostly infilled in place. The sediment analysis of the vibrocores shows a predominantly sandy filling of marine to estuarine origin, evidenced by sponge spicules and a fauna of bivalves and foraminifera adapted to brackish settings. The uppermost deposit exhibits an oxidation profile which marks the groundwater zone transition. Clayey sediments are also present, infilling the uppermost channels and ditches dug during reclamation, in increasing proportions towards the axis of the estuarine palaeovalley. The tidal signature of sedimentary dynamics is evidenced by heterolithic facies in some channel fills and tidal rhythmites infilling scour depressions linked to dike breaching. The abrupt decrease in channel dynamics across the unit boundary, although sedimentation remained sandy in the upper unit, coincides with the development of embankment of the estuarine border and is tentatively interpreted as a result of reclamation.

Abstract Over the past decade, there has been growing interest in the sedimentological community to use micro X‐ray computed tomography to analyse microfacies in sediment cores. However, little attention has been paid to the application of micro‐computed tomography in lithified deposits, even though this can allow their texture to be characterised in three dimensions, providing key information about sedimentary structures. A novel application of micro‐computed tomography in lithified sediment‐gravity flow deposits is presented with the objective of characterising their internal 3D sedimentary structures. This technique is applied to three deep‐marine sandstones showing different compositional properties: Cretaceous Gosau Group (Austria), Eocene Hecho Group (Spain) and the Oligocene Annot Formation (France). From micro‐computed tomography data the size of particles and their distribution throughout the sample is reconstructed in 3D permitting a better visualisation of sedimentary textures. Particle distributions computed from micro‐computed tomography are similar to those computed from thin section image analysis, corroborating the reliability of the micro‐computed tomography to evaluate grain‐size trends. Micro‐computed tomography is complemented with micro‐X‐ray fluorescence and thin section petrographic analyses. In cases where mineral composition or grain size are homogeneous or matrix and grains have similar mineral composition, sedimentary structures do not appear visible from micro‐X‐ray fluorescence or thin section analyses. By separating particles based on their computed tomography density, it is possible to isolate the coarsest fraction, highlighting the sedimentary structures. This study demonstrates (i) the potential of micro‐computed tomography in analyses of sedimentary structures from outcrop data and (ii) the importance of the mineralogical composition and degree of grain sorting in assessing the origin of structureless deposits. Considering the importance of visualising sedimentary structures when interpreting depositional processes, micro‐computed tomography is a new and reliable tool to assess the physical properties of sandstones and to analyse their internal 3D sedimentary structures.

Abstract A tufa mound developed at La Saline Lake, an oxbow of the Athabasca River in the Athabasca Oil Sands deposit of north‐east Alberta, is characterised by an unusual emplacement of a gypsum caprock. This two‐tiered architecture resulted from the bicarbonate‐saturated groundwater flow along Upper Devonian limestone being redirected deeper and encountering the halite–anhydrite dissolution trend within the underlying Middle Devonian Prairie Evaporite Formation, 175 to 200 m below. Migrations up‐section of sulphate‐saturated brine resulted in the gypsum caprock on the tufa mound and discharge of a sulphate‐saturated brine spring with total dissolved solids of ca 80,000 mg/L. The brine spring is bifurcated with flows to the south‐west and north‐west. Calcite–gypsum thrombolytic bottom sediments along the south‐western branch were covered by a halite deposit and subsequently a gypsum crust with a microbial community dominated by the cyanobacteria Coleofasciculus chthonoplastes. The thrombolite contact zone with the halite–gypsum encrustation has a more diversified community with the cyanobacteria Dactylococcopsis. Cyanobacterial mats that wrap around the bulbous gypsum crust protuberances distributed along the brine pool bottom surfaces have significant eukaryotic diversity, represented by the heterotrophic Ochrophyte Paraphysomonas. In contrast, sediments accumulated along the adjacent spring branch flow to the north‐west were thicker and clogged by abundant decomposed and fermented floral debris, unlike the deposit accumulated along the south‐western branch. This resulted in an oxygen‐depleted anaerobic environment dominated by sulphate‐reducing bacteria resulting in a calcite‐rich and sulphate‐starved anaerobic sediment with ca 20% elemental sulphur and emanation of H2S gas.

Abstract Tides are a key driver of a range of Earth system processes, and we now have the capacity to simulate tidal dynamics on a range of temporal and spatial scales. Deep‐time tidal model simulations have been used to provide insight into past ocean circulation patterns, evolution of life and the developments of the Earth‐Moon system's orbital configuration. However, these tidal model simulations are relatively poorly constrained and validated because of a lack of readily available proxies. The feasibility of using two types of proxy is explored here; (1) sedimentary deposits which can directly estimate palaeotidal ranges, and (2) black shale, to constrain three palaeotidal model simulations for different time slices. Specifically, three palaeotidal range proxies were used for the early Devonian (400 Ma), three palaeotidal range proxies and five black shales for the lower Jurassic (185 Ma), and eight black shales for the early Cretaceous (95 Ma). Both tidal proxies confirm the tidal model results in most locations. The model results for 400 Ma and 185 Ma matched 2/3 of the palaeotidal range proxies for each of these periods. The locations of black shale were compared with tidal front locations predicted by the model outputs based on the Simpson–Hunter parameter and the model results from 95 to 185 Ma agree with the black shale proxies in 10/13 of the locations. In the cases where there is a disagreement, the model resolution is probably too low to fully resolve the details of the coastal topography, or—in one case—the palaeobathymetry is incorrect. Consequently, it is argued that it is worth expanding this type of work, and that such data can be used to validate both models and reconstructions.

Abstract Landslides are among the largest mass movements on Earth. As such, the deposits of landslides, also known as mass‐transport deposits, are significant architectural elements of continental margins, especially those receiving sediment from large deltas. Landslide dams have been shown to alter the courses of rivers and submarine channels. However, there are fewer examples of landslides completely filling submarine channels and examples of the subsequent stratigraphic evolution. A three‐dimensional seismic‐reflection dataset (1500 m) Taranaki Basin, offshore the North Island of New Zealand, was used to explore the response of a sequence of channel deposits to landslide filling. The basal channel system initially meandered like a river, with successive channel positions in close proximity, as it aggraded >250 ms two‐way travel time. This systematic, organised evolution is governed by the memory of early channel evolution, which sets the sea floor geomorphology that guides channel‐forming turbidity currents. Later, a channel approximately twice as wide as underlying channels cut off a number of channel bends, probably as a result of an increase in the discharge of channel‐forming turbidity currents. This last channel was filled with submarine landslides, which transported and deposited sediment as debris flows based on the presence of blocks within a matrix comprising chaotic, lower amplitude seismic facies. These debris‐flow deposits smoothed over the sea floor, effectively wiping the memory of channel evolution. As a result, the subsequent channel pattern bears no resemblance to the basal system. Submarine‐channel resetting by landslide filling is common in settings with frequent catastrophic basin‐margin collapses, like offshore New Zealand.

Abstract Seafloor topography can affect turbidity current dynamics on deep‐water slopes, significantly influencing the dispersal of sediment. Despite the common occurrence of topographic complexity, there are few detailed investigations of topographic interactions and their effect on downslope flow evolution in intraslope environments. In this study, the sedimentology and architecture of an Upper Cretaceous intraslope fan succession deposited within an extensional, fault‐bound minibasin are described from a rare, well‐exposed, near‐continuous, oblique depositional‐dip outcrop of the Tres Pasos Formation, Chile. The 2 to 8 m thick studied interval transitions downslope from high‐energy heterolithic strata, including metre‐scale steep‐faced scours, to non‐amalgamated thick‐bedded sandstones. Abrupt increases in sandstone percentage, sandstone bed thickness and grain size occur on the hangingwall blocks of south‐east and north‐east‐dipping normal faults that bound the minibasin. Sandstone beds are dominated by backset or wavy low‐angle stratification proximally, contain compositional banding near faults, and are characterised by increased proportions of planar laminated and structureless turbidite divisions downslope along the transect. Experimental observations of turbidity current interactions with topography are synthesised into a qualitative framework, which is used to interpret flow processes and characteristics from deposit trends. The results reconstruct the response of Froude‐supercritical, stratified turbidity currents with denser basal layers when encountering metre‐scale fault scarps. The analysis shows that metre‐scale topographic features can substantially alter the flow properties of stratified turbidity currents, and their downslope flow evolution to include the development of transitional, depositional and flow‐stripped sediment gravity currents. However, in comparison to base‐of‐slope settings, overall flow conditions are interpreted to be more uniform over slope breaks and zones of flow expansion in a partially confined intraslope environment. These findings have considerable implications for understanding flow response to similar scale morphological features on the seafloor and the potential for flow transformations in intraslope settings.

Abstract The Triassic red beds of the Tabular Cover of the Iberian Meseta are an excellent reservoir outcrop analogue, a direct consequence of high‐quality exposures, which offer exceptional three‐dimensional outcrops, as well as a wide variability of depositional environments. Fluvial and transitional with tide‐influenced and wave‐influenced settings are recognised. Three point bar geobodies of similar scale, but influenced by different processes, were selected from this succession. Point bar geobody 1 was influenced by purely fluvial processes while geobodies 2 and 3 were tide‐influenced. Both types of geobody were developed as point bar deposits in sinuous channels. A fully integrated study was carried out on these geobodies, utilising both outcrop and subsurface‐based approaches, to characterise the key differences between fluvial and tidal point bars in the sedimentary record. The outcrop‐based component involved traditional field data collection methods alongside digital techniques and data capture, including the use of digital outcrop models. Additionally, subsurface‐based methods were employed, utilising core and wireline logs obtained from wells drilled in close proximity to the outcrop. The integration of these approaches aims to accurately differentiate the depositional settings of the three different geobodies, which while apparently very similar in many key respects also exhibit considerable differences when considered from the perspective of subsurface management of potentially similar geobodies. This study also emphasises the need to clearly distinguish high‐sinuosity deposits based on their depositional sub‐environment in order to properly evaluate their potential for subsurface management. Additionally, it highlights the presence and importance of internal baffles that may well influence fluid migration and indeed even compartmentalise geobodies. Three point bar geobodies of similar scale, but influenced by different processes, have been selected in this succession. A fully integrated study was carried out on these geobodies, utilising both outcrop‐based and subsurface‐based approaches, to characterise the key differences between fluvial and tidal point bars in the sedimentary record.

Abstract Using lake‐sediment cores to document past seismicity requires a comprehensive understanding of possible lateral variations in depositional processes. This study aims to reveal the lateral variations in earthquake‐induced event deposits throughout Lake Iznik, a large lake located on the middle strand of the North Anatolian Fault. Based on stratigraphic, sedimentological and geochemical analyses of 14 sediment cores from two subbasins across the lake, five different types of event deposits (T1–T5) were identified and characterised. One event deposit type (T5) is restricted to a delta mouth, characterised by the occurrence of authigenic Fe‐Mn carbonates and interpreted to result from flood events. The four other types of event deposits are characterised by their synchronicity between cores and their age consistency with historical earthquakes and are interpreted to be likely generated by earthquakes. The locally prominent 1065 CE historical earthquake that ruptured the sub‐lacustrine Iznik Fault produced at least three different types of event deposits. One deposit type (T2) is only observed for this very local earthquake, implying that the type of event deposit might also depend on ground‐motion parameters. At the lake scale, the occurrence of various event deposits depends on the flow distance from the source of sediment destabilisations to the coring site.

Abstract The lake‐basin‐type model classified the stratigraphic record of ancient lake systems according to rates of potential accommodation relative to sediment + water supply. The model convolved all modes and paths of water supply (direct fall, surficial, subsurface) with amounts and types of sediment supply (clastic, biogenic, chemical) into a single basin‐filling volume term (sediment + water); its major strength was its widespread applicability. This was supported by subsequent investigations confirming the utility of this approach, but it also revealed some important limitations due to simplifications in the original model. The model has been expanded here to address all inland waters (lakes, ponds, wetlands, playas) as well as adding two major subdivisions of the sediment + water term: (1) water supply paths and (2) the volume of water supply relative to sediment supply. Water supply flow paths in the subsurface are subdivided into ‘throughflow’, ‘recharge’ and ‘discharge’. Each of these groundwater hydrology states can be defined quite precisely by the ratio of net outflow to inflow, from persistently open to consistently closed. These paths can be deciphered using stable carbonate and oxygen isotope composition of primary lacustrine limestones, detailed sedimentology, stratigraphy, palaeontology and mineralogy. Distinguishing water supply paths provides additional insights into playa systems and the occurrence and character of evaporites and carbonates. The volume ratio of water to sediment supply most directly influences the water depths of lakes, ponds and wetlands, which affect water body hydrodynamics and ecosystem behaviour as well as the details of stratal stacking and depositional sequences. It helps fine‐tune estimates of the distribution of sediment texture, bedding, composition and organic matter content. The aim of this contribution is to address questions about the fundamental types of inland water bodies and to explain the new lake‐basin subtypes and provide examples that illustrate their potential to enable higher‐resolution, robust analysis of inland water systems and their stratigraphic records.

Earthquake hazard analyses rely on seismogenic source models. These are designed in various fashions, such as point sources or area sources, but the most effective is the three-dimensional representation of geological faults. We here refer to such models as fault sources. This study presents the European Fault-Source Model 2020 (EFSM20), which was one of the primary input datasets of the recently released European Seismic Hazard Model 2020. The EFSM20 compilation was entirely based on reusable data from existing active fault regional compilations that were first blended and harmonized and then augmented by a set of derived parameters. These additional parameters were devised to enable users to formulate earthquake rate forecasts based on a seismic-moment balancing approach. EFSM20 considers two main categories of seismogenic faults: crustal faults and subduction systems, which include the subduction interface and intraslab faults. The compiled dataset covers an area from the Mid-Atlantic Ridge to the Caucasus and from northern Africa to Iceland. It includes 1248 crustal faults spanning a total length of ∼95 100 km and four subduction systems, namely the Gibraltar, Calabrian, Hellenic, and Cyprus arcs, for a total length of ∼2120 km. The model focuses on an area encompassing a buffer of 300 km around all European countries (except for Overseas Countries and Territories) and a maximum of 300 km depth for the subducting slabs. All the parameters required to develop a seismic source model for earthquake hazard analysis were determined for crustal faults and subduction systems. A statistical distribution of relevant seismotectonic parameters, such as faulting mechanisms, slip rates, moment rates, and prospective maximum magnitudes, is presented and discussed to address unsettled points in view of future updates and improvements. The dataset, identified by the DOI https://doi.org/10.13127/efsm20 (Basili et al., 2022), is distributed as machine-readable files using open standards (Open Geospatial Consortium).

The warming of high mountain regions caused by climate change is leading to glacier retreat, decreasing snow cover, and thawing permafrost, all of which have far-reaching effects on ecosystems and societies. Landsat Collection 2 provides multi-decadal land surface temperature (LST) data, principally suited for large-scale monitoring at high spatial resolution. In this study, we assess the potential to extract LST trends using Landsat 5, 7, and 8 time series. We conduct a comprehensive comparison of both LST and LST trends with data from 119 ground stations of the Intercantonal Measurement and Information System (IMIS) network, located at high elevations in the Swiss Alps. The direct comparison of Landsat and IMIS LST yields robust satellite data with a mean accuracy and precision of 0.26 and 4.68 K, respectively. For LST trends derived from a 22.6-year record length, as imposed by the IMIS data, we obtain a mean accuracy and precision of −0.02 and 0.13 K yr−1, respectively. However, we find that Landsat LST trends are biased due to unstable diurnal acquisition times, especially for Landsat 5 and 7. Consequently, LST trend maps derived from 38.5-year Landsat data exhibit systematic variations with topographic slope and aspect that we attribute to changes in direct shortwave radiation between different acquisition times. We discuss the origin of the magnitude and spatial variation of the LST trend bias in comparison with modeled changes in direct shortwave radiation and propose a simple approach to estimate the LST trend bias. After correcting for the LST trend bias, the remaining LST trend values average between 0.07 and 0.10 K yr−1. Furthermore, the comparison of Landsat- and IMIS-derived LST trends suggests the existence of a clear-sky bias, with an average value of 0.027 K yr−1. Despite these challenges, we conclude that Landsat LST data offer valuable high-resolution records of spatial and temporal LST variations in mountainous terrain. In particular, changes in the mountain cryosphere, such as glacier retreat, glacier debris cover evolution, and changes in snow cover, are preserved in the LST trends and potentially contribute to improved prediction of permafrost temperatures with large spatial coverage. Our study highlights the significance of understanding and addressing biases in LST trends for reliable monitoring in such challenging terrains.

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), for both idealized model experiments and climate projections of different emissions scenarios. We argue that although this approach was practical to allow parallel development of Earth system model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth system models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy, and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently calculated in integrated assessment models (IAMs) during scenario development with only the net carbon emissions passed to the ESM. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use and projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon–climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular, sources and sinks of methane and nitrous oxide) and process-based representation of carbon removal options. These developments will allow three primary benefits: (1) resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts, (2) scenario modeling of the range of possible future climate states including Earth system processes and feedbacks that are increasingly well-represented in ESMs, and (3) optimal utilization of the strengths of ESMs in the wider context of climate modeling infrastructure (which includes simple climate models, machine learning approaches and kilometer-scale climate models).

Arctic sea ice monitoring is a fundamental prerequisite for anticipating and mitigating the impacts of climate change. Satellite-based sea ice observations have been subject to intense attention over the last few decades, with passive microwave (PMW) radiometers being the primary sensors for retrieving pan-Arctic sea ice concentration, albeit with coarse spatial resolutions of a few or even tens of kilometers. Spaceborne synthetic aperture radar (SAR) missions, such as Sentinel-1, provide dual-polarized C-band images with < 100 m spatial resolution, which are particularly well-suited for retrieving high-resolution sea ice information. In recent years, deep-learning-based vision methodologies have emerged with promising results for SAR-based sea ice concentration retrievals. Despite recent advancements, most contributions focus on regional or local applications without empirical studies on the generalization of the algorithms to the pan-Arctic region. Furthermore, many contributions omit uncertainty quantification from the retrieval methodologies, which is a prerequisite for the integration of automated SAR-based sea ice products into the workflows of the national ice services or for assimilation into numerical ocean–sea ice coupled forecast models. Here, we present ASIP (Automated Sea Ice Products): a new and comprehensive deep-learning-based methodology to retrieve high-resolution sea ice concentration with accompanying well-calibrated uncertainties from Sentinel-1 SAR and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive microwave observations at a pan-Arctic scale for all seasons. We compiled a vast matched dataset of Sentinel-1 HH/HV (horizontal transmit, horizontal/vertical receive polarizations) imagery and AMSR2 brightness temperatures to train ASIP with regional ice charts as labels. ASIP achieves an R2 score of 95 % against a held-out test dataset of regional ice charts. In a comparative study against pan-Arctic ice charts and a PMW-based sea ice product, we show that ASIP generalizes well to the pan-Arctic region. Additionally, the comparison reveals that ASIP consistently produces relatively higher sea ice concentration than the PMW-based sea ice product, with mean biases ranging from 1.45 % to 8.55 %, and that the discrepancies are primarily attributed to disparities in the marginal ice zone.

Ice-sheet models used to predict sea-level rise often neglect subglacial hydrology. However, theory and observations suggest that ice flow and subglacial water flow are bidirectionally coupled: ice geometry affects hydraulic potential, hydraulic potential modulates basal shear stress via the basal water pressure, and ice flow advects the subglacial drainage system. This coupling could impact rates of ice mass change but remains poorly understood. We develop a coupled ice–subglacial-hydrology model to investigate the effects of coupling on the long-term evolution of marine-terminating ice sheets. We combine a one-dimensional channelized subglacial hydrology model with a depth-integrated marine-ice-sheet model, incorporating each component of the coupling listed above, yielding a set of differential equations that we solve using a finite-difference, implicit time-stepping approach. We conduct a series of experiments with this model, using either bidirectional or unidirectional coupling. These experiments generate profiles of channel cross-sectional area, channel flow rate, channel effective pressure, ice thickness, and ice velocity. We discuss how the profiles shape one another, resulting in the effective pressure reaching a local maximum in a region near the grounding line. We also describe the impact of bidirectional coupling on the transient retreat of ice sheets through a comparison of our coupled model with ice-flow models that have imposed static basal conditions. We find that including coupled subglacial hydrology leads to grounding-line retreat that is virtually absent when static basal conditions are assumed. This work highlights the role time-evolving subglacial drainage may have in ice-sheet change and informs efforts to include it in ice-sheet models. This work also supplies a physical basis for a commonly used parameterization which assumes that the subglacial water pressure is set by the bed's depth beneath the sea surface.

Quantile mapping is a method often used for the bias adjustment of climate model data toward a reference, i.e. to construct a transformation of the model's distribution to that of the reference. The main moments of the distributions are typically well transformed by quantile mapping, but statistical uncertainty increases towards the extreme tails, making robust transformations challenging. Because of the limited data at the extreme tails, an empirical quantile mapping also needs to make some estimation or fit a parameterised function for data beyond the calibration data range. Here, the MIdAS bias adjustment platform is employed to explore different methods for handling the extreme tail; these approaches are evaluated using an indicator of extreme precipitation – the maximum daily precipitation amount per year. Different methodologies are evaluated for a large ensemble of regional climate model projections over Scandinavia. The sensitivity of the empirical quantile mapping to the tails of the distribution is demonstrated, and it is found that the behaviour is significantly different within and outside of the calibration period, causing severe issues with the temporal consistency of the time series. The sensitivity is identified to be due to differences in the activated features of the bias adjustment within the calibration period (where the empirical transfer function is applied) and outside of that period (where the extrapolation method is likely applied). This means that the bias adjustment method is, in a sense, different between different time periods. Furthermore, finding a robust parameterisation for the tail is not straightforward. We identify a two-step solution that works well for this problem: We refer to the first step as “Murder your darlings”. By excluding data from the tail data in the calibration period, the extrapolation feature is activated for all time periods, even the calibration period. In the second step, applying an outlier-insensitive method for linear regression works well for finding an extrapolation parameterisation for the tail.

Melting calorimetry, a classic experiment often conducted in high-school chemistry laboratories, holds significant untapped potential for scientific applications beyond its educational context. Traditionally, this technique has been applied to measure the liquid water content in snow using two different formulations: melting calorimetry and freezing calorimetry. In contrast to freezing calorimetry, which is considered the reference method for measuring liquid water content, melting calorimetry has been perceived as prone to generating significant inaccuracies. This research revisits the formulations for both melting and freezing calorimeters to assess volumetric liquid water content in snow. By incorporating the calorimetric constant, we account for heat exchange with the calorimeter, a critical factor often neglected in melting-calorimetry experiments. This paper identifies the most effective and least uncertain method for determining this constant. A central contribution of this work is the introduction of a framework for estimating uncertainty in volumetric liquid water content measurements, adhering to established guidelines for uncertainty expression. This novel framework allows us to revisit past mathematical analyses and demonstrate that melting calorimetry delivers reliable measurements with an uncertainty 0.25 % greater than freezing calorimetry. Notably, despite this slightly higher uncertainty, melting calorimetry offers significant practical advantages for field applications. Moreover, we show how the proposed uncertainty framework can be expanded beyond instrumental uncertainty and also take into account the variability from environmental factors and operators, providing a more comprehensive characterization of the uncertainty. By exploiting the proposed uncertainty framework, we finally conduct an in-depth analysis for the optimal tuning of the experiment parameters. This analysis culminates in a robust field protocol for melting calorimetry that transcends commonsense procedural guidelines. Strict adherence to this protocol will maximize measurement accuracy. Applied in field tests in Italy and Switzerland, the melting calorimetry was demonstrated to accurately track the wet front penetration in the snowpacks, producing results comparable to independent dielectric measurements. These findings highlight the accuracy and the practical advantages of melting calorimetry as a reliable field tool for quantifying snowpack liquid water content. Melting calorimetry can potentially serve as a valuable tool for the independent calibration and validation of proximal and remote sensing techniques used for liquid water content retrieval.

The characterization of tropical mountain volcanic red soil in the tropical mountain region, West Lampung area, Sumatra, Indonesia concerning the landslide disaster has been carried out. The research methods used in this research are remote sensing methods, field geological mapping, petrographic analysis (thin section analysis), soil geotechnical analysis, soil geochemical analysis, slope stability analysis, and statistical analysis. The findings indicated that the study area’s volcanic red soil is distinguished by rolling hills with a V-shaped valley, a moderate to severe incline, and an elevation ranging from 850 to 1150 m above sea level. The soil is volcanic residual soil which resulted in wet tropics and from tuff layer and tuffaceous breccias in the felsic composition of the hydrothermal alteration environment. The soil of the study area has a reddish-brown color, and loose characteristic, and belongs to the type of very loose to solid high plasticity uniform inorganic sandy clayey silt. Based on saturated soil slope stability analysis, volcanic red soil has a stable to unstable category if forming a slope. The intrinsic factor that affects the stability of the slope is the percentage of clay content, electrical sensitivity, plasticity index, degree of saturation, and percentage of clay mineral content.

Urban flooding poses a significant threat to vulnerable underground infrastructure systems, such as metro stations. Building collapse induced by earthquakes alters urban building layout and coverage, consequently influencing flood inundation and propagation patterns. This study employs GPU-accelerated hydrodynamic simulation to investigate the mechanisms by which building collapse affects subsequent pluvial or fluvial flooding in the Huangpu District of Shanghai. Massive building collapse layouts are randomly generated, on which hydrodynamic simulations are performed and the inundation process of the metro stations is analyzed. The results reveal that pluvial floods are strongly influenced by localized topography distributed across the city. Consequently, building collapse has a more substantial impact on pluvial flooding when more buildings have collapsed. In contrast, fluvial floods are sensitive to the source location (e.g., location of levee breach) and the long travel route. Building collapse can either positively or negatively influence fluvial flooding by constricting or blocking the flow path. This work highlights the complex mechanism of earthquake–flood multi-hazard processes, emphasizing the importance of performing local-to-local analysis when both the hazard (e.g., individual building collapse, fluvial flood) and the hazard-bearing body (e.g., metro station) are localized. To better serve urban disaster prevention and mitigation, more efforts should be directed to developing physics-based high-resolution urban earthquake–flood simulation methods, as well as to acquiring data to drive such simulations.

Around half of the Earth's soil organic carbon (SOC) is presently stored in the Northern Hemisphere permafrost region. In polar permafrost regions, low temperatures particularly inhibit both the production and biodegradation of organic matter. Under such conditions, abiotic factors such as mesoclimate, pedogenic substrate or altitude are thought to be more important for soil development than biological factors. In Antarctica, biological factors are generally underestimated in soil development due to the rare occurrence of higher plants and the short time since deglaciation. In this study, we aim to assess the relationship between SOC and other soil properties related to the pedogenic factors or properties. Nine plots were investigated along the altitudinal gradient from 10 to 320 m in the deglaciated area of James Ross Island (Ulu Peninsula) using a parallel tea-bag decomposition experiment. SOC contents showed a positive correlation with the content of easily extractable glomalin-related soil protein (EE-GRSP; Spearman r=0.733, P=0.031) and the soil buffering capacity (expressed as ΔpH; Spearman r=0.817, P=0.011). The soil-available P was negatively correlated with altitude (Spearman r=-0.711, P=0.032), and the exchangeable Mg was negatively correlated with the rock fragment content (Spearman r=-0.683, P=0.050). No correlation was found between the available mineral nutrients (P, K, Ca and Mg) and SOC or GRSP. This may be a consequence of the inhibition of biologically mediated nutrient cycling in the soil. Therefore, the main factor influencing nutrient availability in these soils does not seem to the biotic environment; rather, the main impact appears to stem from the abiotic environment influencing the mesoclimate (altitude) or the level of weathering (rock content). Incubation in tea bags for 45 d resulted in the consumption and translocation of more labile polyphenolic and water-extractable organic matter, along with changes in the C content (increase of up to +0.53 % or decrease of up to −1.31 % C) and a decrease in the C:N ratio (from 12.5 to 7.1–10.2), probably due to microbial respiration and an increase in the abundance of nitrogen-binding microorganisms. Our findings suggest that one of the main variables influencing the SOC/GRSP content is not the altitude or coarse-fraction content (for which a correlation with SOC/GRSP was not found); rather, we suspect effects from other factors that are difficult to quantify, such as the availability of liquid water.

Assessing the scale, rate and consequences of climate change, manifested primarily by rising average air temperatures and altered precipitation regimes, is a critical challenge in contemporary scientific research. These changes are accompanied by various anomalies and extreme events that negatively impact ecosystems worldwide. Monoculture forests, including Scots pine (Pinus sylvestris L.) monocultures, are particularly vulnerable to these changes due to their homogeneous structure and simplified ecosystem linkages compared to mixed forests, making them more sensitive to extreme events such as insect outbreaks, droughts, fires and strong winds. In the context of global warming, forest fires are becoming extremely dangerous, and the risk of their occurrence increases as average temperatures rise. The situation becomes even more dramatic when fire enters areas of peatlands, as these ecosystems effectively withdraw carbon from the rapid carbon cycle and store it for up to thousands of years. Consequently, peatlands become emitters of carbon dioxide into the atmosphere. In this study, we aim to trace the last 300 years of historical development of a peatland situated in a Scots pine monoculture. Our focus is on the Okoniny (Jezierzba) peatland located within Tuchola Forest in northern Poland, one of the country's largest forest complexes. We delved into the phase when the peatland's surroundings transitioned from a mixed forest to a pine monoculture and investigated the impact of changes in forest management on the peatland vegetation and hydrology. Our reconstructions are based on a multi-proxy approach using pollen, plant macrofossils, micro- and macro-charcoal, and testate amoebae. We combine the peatland palaeoecological record with the dendrochronology of Pinus sylvestris to compare the response of these two archives. Our results show that a change in forest management and progressive climate warming affected the development of the peatland. We note an increase in acidity over the analysed period and a decrease in the water table over the last few decades that led to the lake–peatland transition. These changes progressed along with the strongest agricultural activity in the area in the 19th century. However, the 20th century was a period of continuous decline in agriculture and an increase in the dominance of Scots pine in the landscape as the result of afforestation. Dendroclimatic data indicate a negative effect of temperature on Scots pine and pressure from summer rainfall deficiency. Additional remote sensing analysis, using hyperspectral, lidar and thermal airborne data, provided information about the current condition of the peatland vegetation. With the application of spectral indices and the analysis of land surface temperature, spatial variations in peatland drying have been identified. Considering the context of forest management and the protection of valuable ecosystems in monocultural forests, the conclusions are relevant for peatland and forest ecology, palaeoecology, and forestry.

Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Drought is a complex climatic phenomenon characterised by water scarcity and is recognised as the most widespread and insidious natural hazard, posing significant challenges to ecosystems and human society. In this study, we propose a new daily based index for characterising droughts, which involves standardising precipitation and/or precipitation minus potential evapotranspiration (PET) data. The new index proposed here, the generalised drought index (GDI), is computed for the entire period available from the Iberian Gridded Dataset (1971 to 2015). Comparative assessments are conducted against the daily Standardised Precipitation Index (SPI), the Standardised Precipitation Evapotranspiration Index (SPEI), and a simple Z-Score standardisation of climatic variables. Seven different accumulation periods are considered (7, 15, 30, 90, 180, 360, and 720 d) with three drought levels: moderate, severe, and extreme. The evaluation focuses mainly on the direct comparison amongst indices in terms of their ability to conform to the standard normal distribution, added value assessment using the distribution added value (DAV), and a simple bias difference for drought characteristics. Results reveal that the GDI, together with the SPI and SPEI, follows the standard normal distribution. In contrast, the Z-Score index depends on the original distribution of the data. The daily time step of all indices allows the characterisation of flash droughts, with the GDI demonstrating added value when compared to the SPI and SPEI for the shorter and longer accumulations, with a positive DAV up to 35 %. Compared to the Z-Score, the GDI shows expected greater gains, particularly at lower accumulation periods, with the DAV reaching 100 %. Furthermore, the spatial extent of drought for the 2004–2005 event is assessed. All three indices generally provide similar representations, except for the Z-Score, which exhibits limitations in capturing extreme drought events at lower accumulation periods. Overall, the findings suggest that the new index offers improved performance and comparatively adds value to similar indices with a daily time step.

Inland saline lakes play a key role in the global carbon cycle, acting as dynamic zones for atmospheric carbon exchange and storage. Given the global decline of saline lakes and the expected increase of periods of drought in a climate change scenario, changes in their potential capacity to uptake or emit atmospheric carbon are expected. Here, we conducted continuous measurements of CO2 and CH4 fluxes at the ecosystem scale in an endorheic saline lake of the Mediterranean region over nearly 2 years. Our focus was on determining net CO2 and CH4 exchanges with the atmosphere under both dry and flooded conditions, using the eddy covariance (EC) method. We coupled greenhouse gas flux measurements with water storage and analysed meteorological variables like air temperature and radiation, known to influence carbon fluxes in lakes. This extensive data integration enabled the projection of the net carbon flux over time, accounting for both dry and wet conditions on an interannual scale. We found that the system acts as a substantial carbon sink by absorbing atmospheric CO2 under wet conditions. In years with prolonged water storage, it is predicted that the lake's CO2 assimilation capacity can surpass 0.7 kg C m2 annually. Conversely, during extended drought years, a reduction in CO2 uptake capacity of more than 80 % is expected. Regarding CH4, we measured uptake rates that exceeded those of well-aerated soils such as forest soils or grasslands, reaching values of 0.2 µmol m−2 s−1. Additionally, we observed that CH4 uptake during dry conditions was nearly double that of wet conditions. However, the absence of continuous data prevented us from correlating CH4 uptake processes with potential environmental predictors. Our study challenges the widespread notion that wetlands are universally greenhouse gas emitters, highlighting the significant role that endorheic saline lakes can play as a natural sink of atmospheric carbon. However, our work also underscores the vulnerability of these ecosystem services in the current climate change scenario, where drought episodes are expected to become more frequent and intense in the coming years.

The World Wide Lightning Location Network (WWLLN) operates a distributed network of stations which detect lightning signals at a planetary scale. Very high currents from lightning strokes radiate strong very low frequency signals in the 6–22 kHz band, which are detected up to 10 000 km away by the WWLLN stations and which are used to determine the time and position of the lightning stroke detected by triangulation, similarly to global positioning systems. Studies of the performance of the WWLLN in different areas around the world have already been reported in the literature, but similar studies for west European regions are still unavailable. This work presents a study to determine the detection efficiency and location accuracy of the WWLLN over Spain by comparing its data with those of the Spanish State Meteorological Agency, AEMET, during 2012 taken as the ground truth. The study provides a detection efficiency for the WWLLN of around 29 % and a location accuracy of between 2 and 3 km. The efficiency for high-energy strokes is considerably higher. A study of four subregions with different geographical features is also considered. The peak current distribution of lightning events in these regions is obtained, and a possible link to the WWLLN performance is discussed. Finally, an application of the WWLLN data for three major storms in 2020, 2021, and 2022 in the Mediterranean area of Spain demonstrates that the WWLLN is well suited for tracking the time evolution of adverse meteorological phenomena.

This study examines the characteristics (magnitudes, trends, and frequency of occurrences) of extreme floods in Nepal, a country that is at significant risk from floods. Daily discharge data from 1980 to 2015 of three gauging stations (Chisapani of Karnali Basin, Devghat of Narayani Basin, and Chatara of Koshi Basin) were used to assess the largest 1 % of flows, the annual top five high flows, and floods of different return periods (2-, 5-, 10-, 20-, and 100-year). In addition, temporal trend analysis of the flood peaks was carried out using the Mann–Kendall test and Sen's slope estimates. Results show that the magnitudes of the largest 1 % flows range from 6310 to 17 900, from 6967 to 12 100, and from 6080 to 9610 m3 s−1 at Chisapani, Devghat, and Chatara, respectively. The monsoon, especially from mid-June to early September, consistently witnesses over 90 % of 1 % extreme flows, with August registering more than 51 % of these occurrences. July and August combine for 81 % of the top five flow events, predominantly in August. Despite insignificant flow changes at a 95 % confidence level, extreme floods (2-, 5-, 10-, 20-, and 100-year return periods) are concentrated heavily in July and August, with August's second fortnight recording the most flood events. This assessment emphasizes July and August as critical months for extreme floods, aiding Nepalese authorities in planning dynamic resource allocation, disaster response, and effective flood management.

Climate change is rapidly altering Himalayan glaciers, jeopardizing downstream water resources. This study investigates the impact of changing air temperatures, precipitation, and glacier configurations on streamflow in the Langtang River basin, a vital Himalayan basin. Using a process-based glacio-hydrological model driven by bias-corrected reanalysis data, we simulate streamflow under various scenarios. Results reveal that, while current glacier conditions show increased runoff with higher temperatures and precipitation, future deglaciation scenarios project a decrease in total streamflow, highlighting the complex interplay between climate and glacier dynamics in basin hydrology. These findings emphasize the need for adaptation strategies to ensure water security in the face of evolving Himalayan hydrology.

Ocean liming has gained attention as a potential solution to mitigate climate change by actively removing carbon dioxide (CO2) from the atmosphere. The addition of hydrated lime to oceanic surface water leads to an increase in alkalinity, which in turn promotes the uptake and sequestration of atmospheric CO2. Despite the potential of this technique, its effects on the marine ecosystem are still far from understood, and there is currently no information on the potential impacts on the concentration and quality of dissolved organic matter (DOM), which is one of the largest, most complex and yet least understood mixtures of organic molecules on Earth. The aim of this study is to provide the first experimental evidence about the potential effects of hydrated lime addition on DOM dynamics in the oceans by assessing changes in its concentration and optical properties (absorption and fluorescence). To investigate the effects of liming on DOM pools with different concentrations and quality, seawater was collected from two contrasting environments: the oligotrophic Mediterranean Sea, known for its dissolved organic carbon (DOC) concentration comparable to that observed in the oceans, and the eutrophic Baltic Sea, characterized by high DOM concentration mostly of terrestrial origin. Hydrated lime was added to both waters to reach pH values of 9 and 10. Our findings reveal that the addition of hydrated lime has a noticeable effect on DOM dynamics in both the Mediterranean Sea and Baltic Sea, determining a reduction in DOC concentration and a change in the optical properties (absorption and fluorescence) of DOM. These effects, detectable at pH 9, become significant at pH 10 and are more pronounced in the Mediterranean Sea than in the Baltic Sea. These potential short-term effects should be considered within the context of the physicochemical properties of seawater and the seasonal variability.

The Glacio-hydrological Degree-day Model (GDM) is a distributed model, but it is prone to uncertainties due to its conceptual nature, parameter estimation, and limited data in the Himalayan basins. To enhance accuracy without sacrificing interpretability, we propose a hybrid model approach that combines GDM with recurrent neural networks (RNNs), hereafter referred to as GDM–RNN. Three RNN types – a simple RNN model, a gated recurrent unit (GRU) model, and a long short-term memory (LSTM) model – are integrated with GDM. Rather than directly predicting streamflow, RNNs forecast GDM's residual errors. We assessed performance across different data availability scenarios, with promising results. Under limited-data conditions (1 year of data), GDM–RNN models (GDM–simple RNN, GDM–LSTM, and GDM–GRU) outperformed standalone GDM and machine learning models. Compared with GDM's respective Nash–Sutcliffe efficiency (NSE), R2, and percent bias (PBIAS) values of 0.80, 0.63, and −4.78, the corresponding values for the GDM–simple RNN were 0.85, 0.82, and −6.21; for GDM–LSTM, they were 0.86, 0.79, and −6.37; and for GDM–GRU, they were 0.85, 0.8, and −5.64. Machine learning models yielded similar results, with the simple RNN at 0.81, 0.7, and −16.6; LSTM at 0.79, 0.65, and −21.42; and GRU at 0.82, 0.75, and −12.29, respectively. Our study highlights the potential of machine learning with respect to enhancing streamflow predictions in data-scarce Himalayan basins while preserving physical streamflow mechanisms.

We have seen a surge in glacio-hydrological modeling efforts in the past few decades. This form of modeling is also being carried out in the Himalayan river basins, but a comprehensive high-resolution simulation software that can be effective with a limited number of hydrometeorological data is recommended. In this regard, an open-source, scalable, flexible, and distributed modeling system called PyGDM has been developed by fully coupling the Glacio-hydrological Degree-day Model with PCRaster Python software. To evaluate the potential of using this model in the Himalayan river basins, we calibrated and then validated the model for Trishuli River basin using geographical data and the existing hydrometeorological data. The tests showed a promising result with respect to the effective application of the model in the entire Himalayan region. The PyGDM source code was optimized and adapted to the process models of glacier melting and hydrological processes in Himalayan basins. It increased the speed of the simulation, made the model highly scalable to accommodate new submodels, and enhanced the flexibility of the model to ingest various types of input data and parameters. Hence, the PyGDM model strives to simulate the glacio-hydrological processes of the entire Himalayan region.

Rivers in the Himalayan and adjacent mountain regions are the lifelines of over 1 billion people and are the backbone of civilizations therein. The short gauge records of Nepal do not provide a sufficient time window to understand the natural variations in river discharge from a long-term climate perspective. By developing a network of over 100 tree-ring chronologies across Nepal, we checked their hydrological sensitivity for long-term streamflow reconstruction. This shows huge potential for long-term annual or seasonal streamflow reconstructions in different river basins of Nepal. A robust reconstruction model was developed between tree growth and streamflow, capturing 56 % of the variance in the actual data, and was used to reconstruct the March–July monthly average streamflow of Sinja Khola (river) at Diware from AD 1700 to 2013. The reconstruction revealed several dry and pluvial periods with the recent decline in the streamflow in the Sinja River. We found short- (2 to 8.7 years) to medium-term (35.2 years) periodicities in the reconstruction that are likely to be associated with climatic oscillations, such as the El Niño–Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the North Atlantic Oscillation (NAO), along with the influence of local circulation patterns. Since Sinja Valley is related to the origin of the Nepali language and civilization, the information on long-term streamflow will be beneficial for water resource management in the context of rapid climate change and for preparedness for water-induced disasters in the region.

Riparian areas serve as interfaces between terrestrial and aquatic (including glaciers and glacial lakes) ecosystems, playing a crucial role in shaping landscapes, supporting flora and fauna diversity, and supporting human communities. Thus, riparian areas maintain ecological, cultural, and socio-economic resilience, enriching communities dependent on these ecosystems. Riparian areas are of great ecological value and have immense potential for tourism. However, the touristic value of riparian zones has largely remained unexplored and is confined mainly to the area of river-based recreational activities. This paper proposes “riparian tourism” as a holistic and sustainable form of tourism that encompasses both consumptive and non-consumptive forms of tourism. The exploration of the subject and the conceptualization of this potentially globally appealing form of tourism have the potential to offer entrepreneurial and touristic opportunities, especially for local communities, thereby ensuring not only ecological but also socio-economic benefits. The paper delves into creating a conceptual framework for riparian tourism, e.g. cryo-tourism. The research in this sense contributes greatly to increasing the discourse on sustainable tourism and emphasizes the urgency to incorporate tourism and conservation actions in riparian areas which are greatly impacted by the changing climate.

During the last few decades, a general increase in heavy rainfall events has been documented in many areas of the world. These events have caused changes in soil erosion rates and strongly affected the human activities in mountain areas by reducing the national income obtained from cultivated land. In this context, the use of fallout radiotracers can be an important tool for better understanding the consequences of climate change in these areas and proposing effective countermeasures in order to reduce soil loss. In this contribution, plot experiments carried out in southern Italy that involve the use of 137Cs and 210Pbex measurements were performed to estimate soil erosion rates during the last few decades. The overall results indicate an increase in soil erosion rates during the last 15–20 years and suggest the use of this technique to detect climate change in mountain areas.

Understanding the hydrology of the Himalayan region and its response to current and future climate scenarios is crucial for identifying the region's future water availability for infrastructural development. For this, the hydropower potential and the impact of future change on the hydrology of the Bheri River basin (BRb) and the Marsyangdi River basin (MRb) were analysed. The Glacio-hydrological Degree-Day Model version 2.0 (GDM V2.0), developed in the PCRaster dynamic modelling framework, was used to simulate the river runoff. Geospatial tools and different criteria were used to assess topographic features, identify suitable places for run-of-river (ROR) hydropower development, and estimate power potential. Eight scenarios with various combinations of temperature and precipitation changes were used to assess the hydropower potential. Increases in temperature by 0.5 and 1 °C (assumed for the near-term and mid-term future) and changes in precipitation of ±10 % and ±20 %, respectively, are used to conduct a sensitivity analysis for the hydropower potential. A total of 116 and 83 suitable sites were identified, and 4242 and 2823 MW power potentials were estimated in the BRb and the MRb, respectively. All the sensitivity scenarios show an increase in hydropower production, except for one with a drier scenario and less precipitation. The integration of a geographic information system (GIS) and a hydrological model helps us to understand the hydrological response to climate variables and its impact on hydropower in the Himalayan region.

In recent decades, the Tsho Rolpa glacial lake has witnessed a significant increase in its surface area. Situated in the Eastern Himalayas at an elevation of 4552 m a.s.l. (meters above sea level), this lake has drawn attention due to the potential risks of glacial lake outburst floods (GLOFs). To comprehensively study and prepare for future GLOF events from Tsho Rolpa, advanced modeling techniques were employed, utilizing the National Weather Service BREACH (NWS-BREACH) and Hydrologic Engineering Center's River Analysis System (HEC-RAS) models. The assessment included the evaluation of dam breach scenarios, especially 20 and 40 m breaches, using the NWS-BREACH model to estimate breach hydrographs. This analysis revealed peak flow rates ranging from 8198 to 26 662 m3 s−1 for the respective breaching scenarios. Additionally, considering a change in the lake area over 20 to 40 years, the peak flow ranged from 8226 to 10 662 m3 s−1 for the 20 m breach scenario. The peak flow estimates obtained from NWS-BREACH were subsequently integrated into the HEC-RAS model to simulate peak discharge and flood heights at varying distances downstream of the lake outlet. To understand the consequences of a GLOF, the impact on downstream areas was assessed through flood inundation maps, and precautionary measures are recommended.

The backwater effect can be caused by a number of factors, including the bridge's pier width and deck level. In lowland regions, the backwater effect can be particularly problematic, as it can lead to flooding and inundation of farmlands and houses. This study examines the impact of bridge structure on the backwater effect in the lowland region of Shreekhandapur, Kavre, Nepal. The study area is characterized by a hill slope and inner river valley, with a gentle river profile that results in low flow velocity and increased deposition. The study compares the backwater effect of an old demolished bridge with four piers of 1.2 m width and abutments on both sides to a new bridge with a single pier of 0.4 m width and a deck level that is 1 m higher. HEC-RAS software was used to analyse the steady flow and create a flood hazard map. The results show that the new bridge with a reduced pier width and increased deck level significantly reduces the backwater effect. The flood hazard map shows that the new bridge along with floodwalls reduces the potential hazard-prone areas by up to 50 %. The findings of this study can be applied to disaster mitigation and bridge design in lowland regions. By reducing pier width and increasing deck level, bridges can be designed to minimize the backwater effect and reduce the risk of flooding.

Snow-induced disasters pose significant risks in mountainous regions. Accurate visibility assessment is crucial for informed decision-making and disaster preparedness. This paper presents an innovative approach that integrates theoretical literature with practical application using augmented reality (AR) to address this challenge. The proposed system, named Him-Drishti, harnesses the established correlation between snowfall intensity and visibility to create a predictive model. By incorporating user-input snowfall intensity predictions, the Him-Drishti AR application dynamically overlays real-time visibility simulations onto the physical environment. Moreover, the use of smartphones further amplifies the practicality of this innovative solution, making the AR application a handy tool, even in the most challenging terrain. This intuitive visualization empowers stakeholders with a comprehensive understanding of potential risks, facilitating informed decisions and optimized disaster response strategies. Through AR visualization, stakeholders, emergency responders, and local authorities gain valuable insights into visibility conditions, enabling them to make informed decisions, take proactive measures, and allocate resources effectively. This study not only enhances the understanding of snow-related disasters but also demonstrates the capacity of AR in disaster management and risk reduction.

The development and integration of the spatial and temporal probabilities of landslides are required for complete landslide hazard mapping at any location. Under changing climate, the computation of the temporal probability of landslides with rainfall magnitude alone is inaccurate. This research proposes a framework based on copula functions to develop a landslide probability map using multi-site rainfall data by accounting for the rainfall variables of intensity and duration using a joint-probability approach. The proposed technique is used for Wayanad District, Kerala, India, considering extreme rainfall events in 2018. Firstly, the landslide susceptibility map of the district was developed using a robust random forest (RF) model. Based on regional geology, geomorphology, and climate, different regions of Wayanad have varying rainfall thresholds assessed according to the intensity and duration of the rainfall. Then, the temporal probability of landslides was developed, accounting for the intensity and duration of rainfall events using the joint-probability estimation using copula. Through the integration of the landslide spatial probability map with the temporal probability, landslide hazard maps (LHMs) for Wayanad were developed for time periods ranging from 1 to 50 years. The results of the study indicate the need for bi- or multi-variate landslide probability modeling in studies on regional landslide hazard assessments.

The present research integrates remote sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Making (MCDM) techniques to identify groundwater potential zones (GWPZs) in Muzaffarpur. Various data sets and study areas were considered to contribute to groundwater availability. The groundwater potential was evaluated, and later, the GWPZ map was validated. It was further categorized into various potential zones from 2005 to 2020. High potential areas, located in gently sloping terrains conducive to high infiltration and percolation, maintained coverage of about 50% of the watershed. Poor potential zones, which represent a small fraction of the area with limited groundwater capacity, showed a consistently low proportion over the years. It highlights the impact of geological and geomorphological factors, particularly the Charnockite Gneiss Complex and sedimentary rocks of the Ganges Basin, on groundwater potential. Soil types, ranging from fine to coarse loamy, play a significant role in groundwater recharge. Rainfall and slope are crucial factors that influence groundwater potential. Higher rainfall and flatter slopes enhance groundwater recharge, emphasizing the importance of variables in assessment. ROC analysis revealed mixed validation results, with zones showing high potential, while others remained poor. It underscores the need for effective water conservation practices to improve groundwater availability.

High Mountain Asia (HMA) is undergoing unprecedented warming, affecting the cryosphere – including permafrost (frozen ground) – and leading to various hazards. However, understanding the prevalence, distribution, and dynamics of these hazards and how they respond to a changing climate is challenging. Permafrost is extensive in HMA, and China makes up a significant portion of this. The permafrost area in China is about 1.6×106 km2, 66 % of which is on the Qinghai–Tibet Plateau. However, most of the scientific literature concerning permafrost in China is published in Chinese and, hence, remains largely unnoticed by the non-Chinese-speaking scientific communities. In this article, we used a systematic review to evaluate the Chinese scientific literature on permafrost-related hazards and found that the studied areas are concentrated in certain areas, especially on the Qinghai–Tibet Engineering Corridor (QTEC). The increasing amount of literature on permafrost hazards reflects the increased impact of climate warming on infrastructure built on permafrost. Not only is permafrost affecting infrastructure; these anthropogenic disturbances themselves also have amplified the occurrence of hazards around settlements and infrastructure. The literature shows the strong relationship between latitude and elevation with permafrost thickness. The permafrost classification system and nomenclature used by Chinese scientists is different to that used elsewhere, which is a potential source of confusion and deserves attention.

Nepal annually invests millions of dollars in hydropower development, with a substantial portion of these funds allocated to civil infrastructure. Climate change, which impacts geological and hydrological conditions, poses a threat to civil components throughout hydropower project construction and operation. This causes budget overruns, project delays, and adverse consequences for society and the environment, ultimately resulting in multimillion-dollar losses. The identification of risk factors and their underlying causes, stemming from the impacts of climate change, constitutes a fundamental aspect of this study. This critical analysis primarily draws upon extensive literature reviews to pinpoint these factors (risk factors arising from climate change), emphasizing their economic and human impacts. This paper highlights the risks to run-of-river hydropower infrastructures in Nepal. The findings of the study can be used to develop and implement adaptation strategies to mitigate the risks posed by climate change to Nepal's vital hydropower sector.

Atmospheric rivers (ARs) are the primary mechanism for transporting water vapor from low latitudes to polar regions, playing a significant role in extreme weather in both the Arctic and Antarctica. With the rapidly growing interest in polar ARs during the past decade, it is imperative to establish an objective framework quantifying the strength and impact of these ARs for both scientific research and practical applications. The AR scale introduced by Ralph et al. (2019) ranks ARs based on the duration of AR conditions and the intensity of integrated water vapor transport (IVT). However, the thresholds of IVT used to rank ARs are selected based on the IVT climatology at middle latitudes. These thresholds are insufficient for polar regions due to the substantially lower temperature and moisture content. In this study, we analyze the IVT climatology in polar regions, focusing on the coasts of Antarctica and Greenland. Then we introduce an extended version of the AR scale tuned to polar regions by adding lower IVT thresholds of 100, 150, and 200 kg m−1 s−1 to the standard AR scale, which starts at 250 kg m−1 s−1. The polar AR scale is utilized to examine AR frequency, seasonality, trends, and associated precipitation and surface melt over Antarctica and Greenland. Our results show that the polar AR scale better characterizes the strength and impacts of ARs in the Antarctic and Arctic regions than the original AR scale and has the potential to enhance communication across observational, research, and forecasting communities in polar regions.

The aim of this study is to identify potential mineral deposits beneath the Southern Benue Trough of Nigeria based on apparent density mapping technique of estimating lateral rock densities from modelled gravity data. In this study, we apply the inverse density deconvolution filter to a short-wavelength gravity component in order to estimate the rock densities for mineral exploration applications and tectonic studies at the Southern Benue Trough in Nigeria. The estimated rock densities vary between 2.50 and 2.74 g/cm3, with minimum density values assigned to volcano-sedimentary deposits along the Cameroon Volcanic Line and maximum density values in the eastern and southern parts associated with mafic igneous rocks. Our gravity and density maps reveal the geometry of dominant geological structures within the study area. The density map highlights carbonate-hosted metallic elements with varying intercalations. Some of these identified mineralized zones coincide with locations of past and present producing mines. Intermediate and mafic igneous rocks as well as highly compacted and volcano-sedimentary rocks are mapped as rock-forming minerals for a mineral exploration. Hence, the obtained model of mineral-bearing rocks mainly demonstrates mechanisms of tectonic events, patterns of deformation regimes, and mineral prospectivity map of the study area.

Abstract Objectives Fully-polarimetric synthetic aperture radar (PolSAR) data contain a rich body of elementary scattering physics information that is critically valuable for a broad range of applications and scientific purposes. However, there is a lack of available high-resolution (