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With mountainous topography and exposure to midlatitude westerly storms causing frequent atmospheric river landfall and associated hydrohazards, medium-range forecasting of extreme precipitation is imperative for New Zealand. Here, the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) is applied to two variables in forecast week 2: total precipitation (TP–EFI) and vertically integrated water vapour transport (IVT–EFI). Results reveal the TP–EFI sometimes outperforms the IVT–EFI in capturing extreme precipitation events – in contrast to past Europe-based research. Importantly, these case studies highlight the need to develop further understanding of sources of predictability for extreme precipitation in different geographical contexts.

The emission of gas species dangerous to human health and life is a widespread source of hazard in various natural contexts. These mainly include volcanic areas but also non-volcanic geological contexts. A notable example of the latter occurrence is the Mefite d'Ansanto area in the southern Apennines in Italy. Here, large emissions of carbon dioxide (CO2) occur at rates that make this the largest non-volcanic CO2 gas emissions area in Italy and probably on Earth. Given the topography of the area, in certain meteorological conditions a cold-gas stream forms in the valleys surrounding the emission zone, which has proved to be potentially lethal to humans and animals in the past. In this study, we present a gas hazard modelling study that considers the main species, CO2, and the potential effect of another notable species, hydrogen sulfide (H2S). For these purposes, we used VolcanIc Gas dIspersion modeLling v1.3.7 (VIGIL), a tool that manages the workflow of gas dispersion simulations in both the dense- and dilute-gas regimes and is specifically optimised for probabilistic hazard applications. In its latest version, VIGIL can automatically detect the most appropriate regime to simulate based on the gas emission properties and meteorological conditions at the source. Results are discussed and presented in the form of maps of CO2 and H2S concentration and persistence at various exceedance probabilities, which consider the gas emission rates and their possible ranges of variation defined in previous studies. The effect of seasonal variations is also presented and discussed.

Heavy-rainfall events and associated natural hazards pose a major threat to rail transport and infrastructure. In this study, the correlation between heavy-rainfall events and three associated natural hazards was investigated using geographic information system (GIS) analyses and random-effects logistic models. The spatiotemporal linkage of a damage database from Deutsche Bahn (DB) Netz AG and the catalogue of radar-based heavy-rainfall events (CatRaRE) from the German Weather Service (DWD) revealed that almost every part of the German rail network was affected by at least one heavy-rainfall event between 2011 and 2021, with 23 % of the flood events, 14 % of the gravitational mass movements, and 2 % of the tree fall events occurring after a heavy-rainfall event. The random-effects logistic regression models showed that a heavy-rainfall event significantly increases the odds of occurrence of a flood (tree fall) by a factor of 22.7 (3.62). We find no evidence of an effect on gravitational mass movements. The heavy-rainfall index and the 21 d antecedent precipitation index were determined to be the characteristics of the heavy-rainfall events with the strongest impact on all three natural hazards. The results underline the importance of gaining more precise knowledge about the impact of climate triggers on natural hazard-related disturbances in order to make rail transport more resilient.

Understanding how water vapor is transported to Antarctica and leads to snowfall is crucial for improving ice-sheet mass balance projections and interpreting ice-core records. Global navigation satellite system (GNSS) receivers distributed across Antarctica to monitor ice velocity and solid Earth motion can be used to understand accumulation, ablation, and snow redistribution at the ice-sheet surface on sub-daily timescales. Here, we present a forward model for reflector height change between the GNSS antenna phase center and the snow surface and an inverse framework to determine accumulation rate and near-surface firn densification from the reflector height time series. We use this model to determine accumulation at three long-term GNSS sites located in the Amundsen Sea Embayment (ASE) and at an array of GNSS receivers deployed in the 2007–2008 and 2008–2009 austral summers. From the GNSS interferometric reflectometry (IR) accumulation time series, we find that extreme precipitation (i.e., the 90th percentile of accumulation events) dominates total precipitation and that extreme event frequency varies seasonally. We use our GNSS-IR accumulation time series together with reanalysis products to characterize the atmospheric conditions that promote extreme snowfall in the ASE. The blocking pressure systems that promote extreme accumulation on Thwaites Glacier are facilitated by tropical teleconnections, specifically convection that promotes Rossby wave trains from the western Pacific, Indian, and Atlantic oceans to the Amundsen and Bellingshausen seas.

Salt weathering, driven by the crystallization of saline solutions within sedimentary rocks, leads to significant material degradation. Key factors influencing this process include salt type, concentration, moisture levels, temperature fluctuations, and pore structure. Environmental conditions and microbial activity further impact weathering, either mitigating or exacerbating its effects. Microorganisms contribute to biological weathering but may also enhance rock properties through biofilm formation or biocementation. Laboratory techniques such as rock testing and micromodel experiments face challenges in replicating complex interactions between microorganisms and salt-bearing porous materials. In this study, we investigated the activity of Paracoccus denitrificans in saline solutions through experiments conducted on Petri dishes, glass slides and micromodels. Key challenges included replicating controlled conditions, managing contamination, and maintaining strict environmental controls. The results highlighted significant challenges in interpreting bacterial activity within salt-bearing systems, particularly due to contamination risks and difficulties in maintaining precise experimental conditions. Additionally, experimental setups, such as fluid actuation using laser light beams, were found to introduce further complexities. This research provided recommendations and emphasized the critical need for refined methodologies to enhance accuracy and reliability in future studies.

Planktic foraminifera are key producers of pelagic carbonate, and their shell weight is suggested to have been influenced by the environment in which they calcify. However, there is debate about the use of size-normalised weight (SNW) as a proxy, as some authors invoke a carbonate system control on calcification (and by extension SNW as a pCO2 proxy), while others suggest that species optimum conditions, nutrient concentration, or temperature drive shell weight. To better understand this proxy, we investigate what drives SNW and whether discrepancies in the proposed control on weight are due to differing data collection methodologies and/or regionally different drivers. We integrate new and published SNW data with environmental hindcast data from the CMIP6 modelling suite. Using Bayesian regression modelling, we find that the environment alone does not explain the variability in SNW across species. Although physiology likely modulates the response to the environment, we find little evidence of a unifying driver at the ecogroup level. Instead, we identify species-specific responses associated with drivers including (but not limited to) the carbonate system, which are likely different between ocean basins. We hypothesise that this is partly influenced by cryptic species and regional phenotypic plasticity in changes to shell weight that are not well understood, such as the thickness of calcite deposited during some species' reproductive phases. Consequently, which species to use as a pCO2 proxy or whether multiple species should be used in parallel to reduce uncertainty should be carefully considered. We strongly encourage the regional testing and calibration of pCO2–SNW relationships.

Various methods are available to measure water storage across different landscape compartments, e.g. cosmic-ray neutron sensing, remote sensing, or hydrogravimetry. All these methods provide integral estimates that are representative of their corresponding measurement volume. However, we typically do not know the true value of water storage in these measurement volumes, which makes it difficult to assess the accuracy of such methods. In this study we suggest a synthetic virtual landscape that allows for an exact definition of all variables of interest and, consequently, constitutes the so-called “virtual truth” free of knowledge gaps. Such a landscape can be explored in various “virtual field campaigns” using “virtual sensors” that mimic the response and characteristics of actual devices. We use dedicated physically based models to simulate the signal a sensor would receive. These model outputs, termed “virtual observations”, can be explored and also allow for the reconstruction of water storage, which can then readily be compared to the virtual truth. Insights from this comparison could help to better understand real measurements and their uncertainties and to challenge accepted knowledge about signal processing and data interpretation. The Virtual Joint Field Campaign is an open collaborative framework for constructing such landscapes. It comprises data and methods to create and combine different compartments of the landscape (e.g. atmosphere, soil, vegetation). The present study demonstrates virtual observations of water storage with cosmic-ray neutron sensing, hydrogravimetry, and remote sensing in three exemplary landscapes. It enables unprecedented opportunities for the systematic assessment of the sensor's strengths and weaknesses and even their combined use.

All hydrocarbon (HC) reservoirs leak to some extent. When small quantities of HCs escape offshore reservoirs and migrate through overlying organic-poor marine sediments towards the surface, these HCs are often completely metabolized by microorganisms before reaching the sediment–water interface. However, these low and often unnoticed upward HC fluxes still influence the geochemistry of surrounding sediments and potentially stimulate metabolic activity by microbial populations in shallow subseafloor environments. In this study, we examined how localized HC seepage affects microbial sulfate reduction in organic-poor sediments from the SW Barents Sea, focusing on three sampling areas overlying known HC deposits and two pristine seabed reference areas. The analysis of 50 gravity cores revealed significant variability in the predicted sulfate depletion depth, ranging from 3 to 12 m below the seafloor. We observed nearly linear pore water sulfate and alkalinity profiles, alongside low rates of sulfate reduction (pmol cm3 d−1). Metagenomic and metatranscriptomic data indicated metabolic potential and activity towards sulfate reduction and anaerobic oxidation of methane (AOM). Expression of functional marker genes (aprAB, dsrAB, mcrA) revealed metabolic activities by sulfate-reducing Desulfobacterota and methanotrophic ANME-1 archaea sustained by HC traces in the sediment. Furthermore, in concomitance to AOM processes, we found that archaea amongst the classes Lokiarchaeia and Thorarchaeia were expressing genes involved in sulfur reduction (hydB, hydG). Overall, our study demonstrates that the gradient in pore water geochemistry, the rates of sulfate reduction processes, and the genetic features of microbial populations actively involved in sulfate-driven AOM processes are all affected by low and often unnoticed upward HC fluxes. This slight HC seepage resulted in sulfate depletion at shallower depths compared to what would be expected at a comparable non-affected site and produced concomitant biogeochemical signatures in the shallow subsurface that enable the inference of deeply buried reservoirs.

A parsimonious model based on Dalton's law reveals substomatal cavities to be dilute in oxygen (O2), despite photosynthetic O2 production. Transpiration elevates the partial pressure of water vapour but counteractively depresses the partial pressures of dry air's components – proportionally including O2 – preserving cavity pressurization that is negligible as regards air composition. Suppression of O2 by humidification overwhelms photosynthetic enrichment, reducing the O2 molar fraction inside cool or warm leaves by hundreds or thousands of parts per million. This elucidates the mechanisms that realize O2 transport: diffusion cannot account for up-gradient conveyance of O2 from dilute cavities through stomata to the more aerobic atmosphere. Rather, leaf O2 emissions depend on non-diffusive transport via mass flow forced by cavity pressurization, which is not negligible in the context of dynamics. Non-diffusive O2 expulsion overcomes massive inward O2 diffusion to force net O2 emission. At very high leaf temperatures, mass flow also influences transport of water vapour and carbon dioxide, physically decoupling their exchanges and reducing water-use efficiency, independently of stomatal regulation.

Accurate flood risk assessments and early warning systems are needed to protect and prepare people in coastal areas from storms. In order to provide this information efficiently and on time, computational costs in flood models need to be kept as low as possible. One way to achieve this goal is to apply subgrid corrections to relatively coarse computational grids. Previously, these have been used in full-physics circulation models. In this paper, for the first time, we developed subgrid corrections for the linear inertial equations (LIEs) that account for bed level and friction variations. They were implemented in the Super-Fast INundation of CoastS (SFINCS) model version 2.1.1 Dollerup release. Pre-processed lookup tables that correlate water levels with hydrodynamic quantities make more precise simulations with lower computational costs possible. These subgrid corrections have undergone validation through several conceptual and real-world application scenarios, including rainfall-induced flooding during a hurricane and tidal propagation in an estuary. We demonstrate that the subgrid corrections for linear inertial equations significantly improve model accuracy while utilizing the same resolution without subgrid corrections. In terms of computational efficiency, subgrid corrections increase computational costs by 38 %–128 %. However, this yields a 35–50-time speedup since coarser model resolutions with subgrid corrections can provide the same accuracy as finer resolutions without subgrid corrections. Limitations are also discussed; for example, when grids do not adequately resolve river meanders, fluxes can be overestimated. Our findings show that subgrid corrections are a useful asset for hydrodynamic modelers striving to achieve a balance between accuracy and efficiency.

Extreme precipitation events (EPEs) potentially present an enormous societal risk and often lead to major human and economic impacts. In the mid-latitudes, such EPEs are often triggered by intense extratropical cyclones and their associated frontal systems. Over the last decade, several studies have shown the important and specific role played by atmospheric rivers (ARs) in the occurrence of EPEs in western Europe, particularly in the Iberia Peninsula. In this study we analyze the all-time 24 h record-breaking precipitation (120.3 mm) recorded in the historical Dom Luiz Observatory (records since 1863) in Lisbon, Portugal, between 12 and 13 December 2022. A synoptic evaluation of surface and upper-level fields from 5 to 14 December is performed using the European Centre for Medium-Range Forecasts (ECMWF) Reanalysis v5 (ERA5). The week before the EPE, there was a combined effect of a large-scale sea-level-pressure (SLP) gradient resembling the North Atlantic Oscillation (NAO) negative phase, a southerly position of the jet stream, and above-normal positive sea surface temperature (SST) anomalies over the North Atlantic that led to the development of several low-pressure systems at relatively low latitudes, all traveling along the same mean path towards western Europe. The atmospheric river associated with this event was first detected late on 10 December, associated with a deep extratropical cyclone. The combination of high integrated vapor transport (and moisture inflow by the warm conveyor belt), with a dynamical component characterized by a suitable uplift motion allowed the system to evolve and maintain its AR characteristics for 72 h. The extratropical cyclone and associated AR moved northeast towards Iberia, making landfall in Portugal on 12 December as an extreme AR event, leading to the 24 h record-breaking precipitation event.

The southern Finland granites and associated migmatitic rocks have a complex metamorphic history, being affected by multiple events during the ca. 1.88–1.79 Ga Svecofennian orogeny. In this study, the prolonged tectonic evolution of migmatites and associated rocks in southwestern Finland has been investigated using the new in situ Lu–Hf method. Results reveal detailed temporal constraints for the tectonic evolution that can be linked to major events in adjacent tectonic blocks in both Finland and Sweden during the Svecofennian orogeny. The metamorphic peak at the Olkiluoto site occurred at 1829 ± 19 Ma based on in situ Lu–Hf dating of garnet. The pressure–temperature (P–T) path for the rocks indicates a prograde evolution, with peak P–T conditions of 3–5 kbar and approximately 700 °C. Younger ages of ca. 1780 Ma obtained using both Lu–Hf and U–Pb systems in apatite inclusions in garnet indicate rapid cooling at 1780 Ma. Based on the metamorphic constraints and obtained ages, we link the Olkiluoto site to the Häme orogenic belt in southern Finland and also support the proposed thermal–tectonic connection with the Ljusdal lithotectonic unit in central Sweden.

Studying social impacts of and responses to historical extreme climate events can offer valuable insights into coping with major disaster events and adapting to climate change better. This paper developed a model of the processes and responses to extreme drought-induced famines in ancient China. Based on this, the study explored the differences in famine causation and response effectiveness between the Chenghua drought (1483–1486 CE) and Wanli drought (1585–1588 CE). The findings are as follows: (1) by the time of the Wanli drought, the increase in land reclamation had enhanced societal defence, preventing many drought-affected counties from experiencing famine. Even in cases where famines did occur, their severity was lower than during the Chenghua drought. (2) State emergency measures, including exemption and relief, proved effective in mitigating famines. The stronger finance and economy during the Wanli drought enabled more robust relief efforts, resulting in lower famine severity. (3) Famine response capabilities varied regionally. Shandong, Beijing, Tianjin, and Hebei demonstrated strong defensive capabilities and effective state emergency responses, while Shanxi had weaker defensive abilities, making it more vulnerable to famine. The defensive capabilities in Henan, Shaanxi, Gansu, and Ningxia showed significant improvement.

During the Atlantic References and Convection (ARC) ship campaign with the reference MSM114/2, which took place in early 2023, the German research vessel Maria S. Merian travelled from Mindelo, Cape Verde, to Punta Arenas, Chile. One of the main objectives of ARC was to obtain vertically resolved cross sections of the Intertropical Convergence Zone (ITCZ). To this end, we crossed the ITCZ three times in the meridional direction. We present the atmospheric and oceanographic measurements collected during ARC in a standardised way to facilitate working with data from different instruments and to make the data easily accessible. This approach is not limited to ARC but could serve as a prototype for future (and past) ship campaigns. We present data from the integrated ship sensors (DSHIP); a humidity and temperature profiler (HATPRO); a ceilometer; aerosol instruments (DustTrak, Microtops, and Calitoo); radiosondes; uncrewed aircraft vehicles (UAVs); and conductivity, temperature, and depth (CTD) profiles of the upper ocean. We distinguish between temporal continuous data (DSHIP, HATPRO, Ceilometer, and DustTrak) from point measurements (radiosondes, UAVs, CTDs, Calitoo, and Microtops). To illustrate the data sets provided, we present examples of measurements taken during the three crossings of the ITCZ and during a storm in the Roaring Forties in the South Atlantic at the end of the campaign. An overview of all available data sets, including DOIs and download links, can be found in Köhler et al. (2024a) with the DOI https://doi.org/10.1594/PANGAEA.966616. For references to the individual data sets, please refer to the “Data availability” section.

Soil respiration (Rs) is an important carbon flux in terrestrial ecosystems, and knowledge about this CO2 release process and the drivers involved is a key topic in the context of global change. However, temporal and spatial variability has not been studied extensively in semi-arid systems such as olive groves. In this study, we show a full year of continuous measurements of Rs with six automatic chambers in a fertigated olive grove with bare soil in the Mediterranean accompanied by modeled ecosystem respiration (Reco) estimated by decomposing net ecosystem exchange (NEE) measured using the eddy covariance (EC) technique. To study spatial variability, the automatic chambers were distributed equally under the canopy (Rs Under-Tree) and in the center of the alley (Rs Alley), and the gradient of Rs between both locations was measured in several manual campaigns in addition to angular changes about the olive trees. The results indicate that Rs Under-Tree was 3 times higher than Rs Alley in the annual computations. Higher Rs was found on the southern face, and an exponential decay of Rs was observed until the alley's center was reached. These spatial changes were used to weigh and project Rs onto the ecosystem scale, whose annual balance was 1.6–2.3 times higher than the Reco estimated using EC-derived models. Rs Under-Tree represented 39 % of the Rs of the olive grove. We found values of Q10 in the vicinity of the olive tree in the warm period. Outbursts of CO2 emissions associated with precipitation events were detected, especially in the alley, during dry periods and after extended periods without rain, but they were not accurately detected by EC-derived respiration models. We point out an interaction between several effects that vary in time, that are different under the canopy than in the alleys, and that the accepted models for estimating Q10 and Reco do not consider. These results show high spatial and temporal heterogeneity in soil respiration and the factors involved, which must be considered in future works in semi-arid agroecosystems.

Avalanche forecasting is a human judgment process with the goal of describing the nature and severity of avalanche hazard based on the concept of distinct avalanche problems. Snowpack simulations can help improve forecast consistency and quality by extending qualitative frameworks of avalanche hazard with quantitative links between weather, snowpack, and hazard characteristics. Building on existing research on modeling avalanche problem information, we present the first spatial modeling framework for extracting the characteristics of storm and persistent slab avalanche problems from distributed snowpack simulations. The grouping of simulated layers based on regional burial dates allows us to track them across space and time and calculate insightful spatial distributions of avalanche problem characteristics. We applied our approach to 10 winter seasons in Glacier National Park, Canada, and compared the numerical predictions to human hazard assessments. Despite good agreement in the seasonal summary statistics, the comparison of the daily assessments of avalanche problems revealed considerable differences between the two data sources. The best agreements were found in the presence and absence of storm slab avalanche problems and the likelihood and expected size assessments of persistent slab avalanche problems. Even though we are unable to conclusively determine whether the human or model data set represents reality more accurately when they disagree, our analysis indicates that the current model predictions can add value to the forecasting process by offering an independent perspective. For example, the numerical predictions can provide a valuable tool for assisting avalanche forecasters in the difficult decision to remove persistent slab avalanche problems. The value of the spatial approach is further highlighted by the observation that avalanche danger ratings were better explained by a combination of various percentiles of simulated instability and failure depth than by simple averages or proportions. Our study contributes to a growing body of research that aims to enhance the operational value of snowpack simulations and provides insight into how snowpack simulations can help address some of the operational challenges of human avalanche hazard assessments.

Manganese (Mn) is an essential micronutrient and key redox intermediate in marine systems. The role of organically complexed dissolved Mn(III) (dMn(III)-L) as an electron acceptor and donor in marine environments is still incompletely understood. Here, we use geochemical depth profiles of solutes and solids for the sediment and overlying waters and a reactive transport model to reconstruct the seasonality in sedimentary dMn(III)-L dynamics and benthic Mn release in a eutrophic, seasonally euxinic coastal basin (Lake Grevelingen, the Netherlands). Our model results suggest that dMn(III)-L is a major component of the dissolved Mn pool throughout the year. According to the model, there are three major sources of pore water dMn(III)-L when oxygen (O2) is present in the bottom water, namely reduction of Mn oxides coupled to the oxidation of Fe(II), reduction of Mn oxides coupled to organic matter degradation, and oxidation of Mn(II) with O2. Removal of pore water dMn(III)-L is inferred to primarily take place through reduction by dissolved Fe(II). When bottom waters are euxinic in summer, model-calculated rates of sedimentary Mn cycling decrease strongly because of a lower supply of Mn oxides. The dMn(III)-L transformations in summer mostly involve reactions with Fe(II) and organic matter. Modeled benthic release of Mn mainly occurs as dMn(III)-L when bottom waters are oxic, as Mn(II) upon initial bottom-water euxinia and as both Mn(II) and dMn(III)-L when the euxinia becomes persistent. Our model findings highlight strong interactions between the sedimentary Fe and Mn cycles. Dissolved Mn(III)-L is a relatively stable and mobile Mn species, compared to Mn(II), and is therefore more easily transported laterally throughout the coastal zone and possibly also to open marine waters.

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

Soils are the largest terrestrial carbon (C) pool on the planet, and targeted grassland management has the potential to increase grassland C sequestration. Appropriate land management strategies, such as organic matter addition, can increase soil C stocks and improve grasslands' resilience to drought by improving soil water retention and infiltration. However, soil carbon dynamics are closely tied to vegetation responses to management and climatic changes, which affect roots and shoots differently. This study presents findings from a 3-year field experiment on two Swedish grasslands that assessed the impact of compost amendment and experimental drought on plant biomass and soil C to a depth of 45 cm. Aboveground biomass and soil C content (% C) increased compared with untreated controls in compost-amended plots; however, because bulk density decreased, there was no significant effect on soil C stocks. Experimental drought did not significantly reduce plant biomass compared to control plots, but it stunted the increase in aboveground biomass in compost-treated plots and led to changes in root traits. These results highlight the complexity of ecosystem C dynamics and the importance of considering multiple biotic and abiotic factors across spatial scales when developing land management strategies to enhance C sequestration.

Utilising the 20th Century Reanalysis version 3 (20CRv3), we examine changes in the extent and rate of autumn Eurasian snow cover (SC) advance and the temporal variability in the SC–Arctic Oscillation (AO) relationship. Novel aspects are (i) analysis back to 1836, (ii) adjusting the reanalysis SC through comparison with observations, and (iii) analysing the statistical significance of the frequency of periods of significant SC–AO relationships to determine whether these connections can be distinguished from stochastic processes. Across the full span of 20CRv3, there is a small increase in mean September Eurasian SC. In contrast, there have been significant decreases in both October and November SC. Trends over the past 50 years demonstrate a slowing and accelerating of snow advance in October and November, respectively, corresponding to a postponement of SC onset. Robust relationships exist between September and October Eurasian SC and the winter AO across the 180-year span of 20CRv3. Within Eurasia, we reveal a strong SC–AO relationship with September SC in northeastern Eurasia, which has not been noted previously. The associated spatial pattern of September tropospheric height anomalies closely matches the positive phase of the western Pacific teleconnection pattern. As many other factors are known to impact the winter AO, and these predominantly occur in October or November, the residual September SC signal-to-noise ratio in the winter atmosphere is small. Therefore, model experiments in which only the magnitude of September SC is perturbed will be necessary to elucidate the processes behind this newly described SC–AO relationship.

Timely and accurate high-resolution annual mapping of rice distribution is essential for food security, greenhouse gas emissions assessment, and support of sustainable development goals. East Asia (EA), a major global rice-producing region, accounts for approximately 29.3 % of the world's rice production. Therefore, to acquire the latest rice distribution of the EA, this study proposed a novel rice distribution mapping method based on the Google Earth Engine (GEE) platform, producing a 10 m resolution annual rice distribution map (EARice10) of EA for 2023. A new synthetic aperture radar (SAR)-based rice distribution mapping index (SRMI) was firstly proposed and combined with optical indices to generate representative rice samples. In addition, a stacking-based optical–SAR adaptive fusion model was designed to fully integrate the features of Sentinel-1 and Sentinel-2 data for high-precision rice mapping in EA. The accuracy of EARice10 was evaluated using more than 90 000 validation samples and achieved an overall accuracy of 90.48 %, with both the user accuracy and the producer accuracy exceeding 90 %. The reliability of the product was verified by R2 values ranging between 0.94 and 0.98 with respect to official statistics and between 0.79 and 0.98 with respect to previous rice mapping products. EARice10 is accessible at https://doi.org/10.5281/zenodo.13118409 (Song et al., 2024).

Many debris-flow catchments pose an underappreciated hazard, especially where there are dwellings on debris-flow fans and other depositional areas. There is a need to make communities and those involved in community governance aware of situations where there may be a credible risk to life from debris flows. This needs to be simple and cheap to do, since funding is often not available to study unrecognised natural hazards. Here, we use published models to (1) estimate the threshold annual recurrence interval (ARI) for debris flows in a catchment, below which there is an unacceptable annual risk to life for the occupants of any dwellings, and (2) identify the “window of non-recognition” where debris flows are sufficiently infrequent within a catchment that it is not recognised as susceptible yet frequent enough that the risk to life exceeds the acceptability threshold. Using four Aotearoa New Zealand (NZ) studies, we estimate a 95 % credible interval range for the ARIs of life-threatening debris flows of between 100 and 500 years. We show that given these credible intervals and precautionary but realistic assumptions about debris-flow behaviour and the vulnerability of dwellings and their occupants, catchments with no history of debris-flow activity can pose an unrecognised and unacceptable annual risk to life (P=0.256 that the annual risk-to-life threshold of 1 in 1000 is exceeded).

In recent years, opportunities have opened up to develop and validate glacier models in regions that have previously been infeasible due to observation and/or computational constraints thanks to the availability of globally capable glacier evolution modelling codes and spatially extensive geodetic validation data. The glaciers in the tropical Andes represent some of the least observed and modelled glaciers in the world, making their trajectories under climate change uncertain. Studies to date have typically adopted empirical models of the surface energy balance and ice flow to simulate glacier evolution under climate change, but these may miss important non-linearities in future glacier mass changes. We combine two globally capable modelling codes that provide a more physical representation of these processes:(i) the Joint UK Land Environment Simulator (JULES), which solves the full energy balance of snow and ice, and (ii) the Open Global Glacier Model (OGGM), which solves a flowline representation of the shallow-ice equation to simulate ice flow. JULES–OGGM is applied to over 500 tropical glaciers in the Vilcanota-Urubamba basin in Peru, home to more than 800 000 people that predominantly live in rural communities with low socioeconomic development and high vulnerability to climate change. The model is evaluated against available glaciological and geodetic mass balance observations to assess the potential for using the modelling workflow to simulate tropical glacier evolution over decadal timescales. We show that the JULES–OGGM model can be parameterized to capture decadal (2000–2018) mass changes in individual glaciers, but we also show that limitations in the JULES prognostic snow model prevent accurate replication of observed surface albedo fluctuations and mass changes across all glaciers simultaneously. Specifically, the model cannot replicate the feedbacks between the driving meteorology, surface energy balance, ablation processes, and snow darkening. Only by forcing the model with observed net radiation variables were we able to capture observed surface albedo dynamics. When driven with statistically downscaled climate change projections, the JULES–OGGM simulations indicate that, contrary to point-scale energy balance studies, sublimation plays a very minor role in glacier evolution at the basin scale and does not bring about significant non-linearities in the glacier response to climate warming. The ensemble mean simulation estimates that total glacier mass will decrease to 17 % and 6 % of that in 2000 by 2100 for Representative Concentration Pathway (RCP) 4.5 and RCP8.5, respectively, which is more conservative than estimates from some other global glacier models.

In geosciences, including hydrology and geomorphology, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. Traditional calibration techniques, however, are marked by poor generalizability, demanding significant manual labor for data preparation and the calibration process itself. Moreover, the utility of machine-learning-based and data-driven approaches is curtailed by the requirement for the numerical model to be differentiable for optimization purposes, which challenges their generalizability across different models. Furthermore, the potential of freely available geomorphological data remains underexploited in existing methodologies. In response to these challenges, we introduce a generalizable framework for calibrating numerical models, with a particular focus on geomorphological models, named Iterative Model Calibration (IMC). This approach efficiently identifies the optimal set of parameters for a given numerical model through a strategy based on a Gaussian neighborhood algorithm. Through experiments, we demonstrate the efficacy of IMC in calibrating the widely used landscape evolution model CAESAR-Lisflood (CL). The IMC process substantially improves the agreement between CL predictions and observed data (in the context of gully catchment landscape evolution), surpassing both uncalibrated and manual approaches.

Seismic facies classification is crucial for seismic stratigraphic interpretation and hydrocarbon reservoir characterization but remains a tedious and time-consuming task that requires significant manual effort. Data-driven deep-learning approaches are highly promising for automating the seismic facies classification with high efficiency and accuracy, as they have already achieved significant success in similar image classification tasks within the field of computer vision (CV). However, unlike the CV domain, the field of seismic exploration lacks a comprehensive benchmark dataset for seismic facies, severely limiting the development, application, and evaluation of deep-learning approaches in seismic facies classification. To address this gap, we propose a comprehensive workflow to construct a massive-scale benchmark dataset of seismic facies and evaluate its effectiveness in training a deep-learning model. Specifically, we first develop a knowledge graph of seismic facies based on geological concepts and seismic reflection configurations. Guided by the graph, we then implement the three strategies of field seismic data curation, knowledge-guided synthesization, and generative adversarial network (GAN)-based generation to construct a benchmark dataset of 8000 diverse samples for five common seismic facies. Finally, we use the benchmark dataset to train a network and then apply it to two 3-D seismic data for automatic seismic facies classification. The predictions are highly consistent with expert interpretation results, demonstrating that the diversity and representativeness of our benchmark dataset are sufficient to train a network that can be generalized well in seismic facies classification across field data. We have made this dataset (https://doi.org/10.5281/zenodo.10777460, Gao et al., 2024a), the trained model, and the associated codes (https://doi.org/10.5281/zenodo.13150879, Gao et al., 2024b) publicly available for further research and validation of intelligent seismic facies classification.

Environmental assets provide important benefits to society and support the equilibrium of natural processes. They can be affected by floods; however, flood risk analyses usually neglect environmental areas due to (i) a lack of agreement on what should be considered an environmental asset, (ii) a poor understanding of environmental values, and (iii) the absence of damage models. The aim of this work is to advance the understanding of environmental exposure to river floods by first identifying asset typologies that could be considered in flood risk analyses and second by introducing a method, named EnvXflood, to estimate flood exposure qualitative values of environmental assets. The method is structured around three levels of detail requiring increasing information, from a fast and minimal-resource analysis suitable for regional assessment to a detailed ecosystem-service-based site analysis. Exposure focuses on the social and environmental value of the assets. Social values were investigated by means of a participatory approach. The method was tested on three case studies in Italy (the Tuscany region, Chiana Basin, and Orcia Basin). The ecosystem service weighting obtained from the participatory approach highlights the perceived leading importance of the biodiversity-supporting service. The results of the analyses show that environmental assets related to water, such as rivers, lakes, and wetlands, are the most exposed to floods. However, they are commonly not considered exposed assets in typical river management practices. Further research should aim at consolidating the asset typologies to be included in environmental exposure analysis and their social and ecological value, moving towards a coherent understanding of environmental flood impacts.

Accurate representation of croplands is essential for simulating terrestrial water, energy, and carbon fluxes over India because croplands constitute more than 50 % of the Indian land mass. Wheat and rice are the two major crops grown in India, covering more than 80 % of the agricultural land. The Community Land Model version 5 (CLM5) has significant errors in simulating the crop phenology, yield, and growing season lengths due to errors in the parameterizations of the crop module, leading to errors in carbon, water, and energy fluxes over these croplands. Our study aimed to improve the representation of wheat and rice crops in CLM5. Unfortunately, the crop data necessary to calibrate and evaluate the models over the Indian region are not readily available. This study used comprehensive wheat and rice novel crop data for India created by digitizing historical observations. This dataset is the first of its kind, covering 50 years and over 20 sites of crop growth data across tropical regions, where data have traditionally been spatially and temporally sparse. We used eight wheat sites and eight rice sites from the recent decades. Many sites have multiple growing seasons, taking the total up to nearly 20 growing seasons for each crop. We used these data to calibrate and improve the representation of the sowing dates, growing season, growth parameters, and base temperature in CLM5. The modified CLM5 performed much better than the default model in simulating the crop phenology, yield, and carbon, water, and energy fluxes compared to site-scale data and remote sensing observations. For instance, Pearson's r for monthly leaf area index (LAI) improved from 0.35 to 0.92, and monthly gross primary production (GPP) improved from −0.46 to 0.79 compared to Moderate Resolution Imaging Spectroradiometer (MODIS) monthly data. The r value of the monthly sensible and latent heat fluxes improved from 0.76 and 0.52 to 0.9 and 0.88, respectively. Moreover, because of the corrected representation of the growing seasons, the seasonality of the simulated irrigation matched the observations. This study demonstrates that global land models must use region-specific parameters rather than global parameters for accurately simulating vegetation processes and corresponding land surface processes. The improved CLM5 can be used to investigate the changes in growing season lengths, water use efficiency, and climate impacting crop growth of Indian crops in future scenarios. The model can also help provide estimates of crop productivity and net carbon capture abilities of agroecosystems in future climate.

Over the last 40 years (1980–2020), 159 people died in inland floods in Germany. The flood of 2021 caused 190 flood fatalities in Germany, 134 of them in the Ahr valley. We investigate what made this event so deadly in order to help improve flood risk management and prevent future fatalities. A comprehensive analysis of the factors influencing the occurrence of fatalities is carried out on the basis of the death investigation files of the public prosecutor's office. This unprecedented flash flood was characterised by high water levels and high flow velocities. The extent of inundation in 2021 far exceeded the official hazard map for the extreme flood scenario. Additionally, early warning and evacuation were inadequate, so many people were surprised by the flash flood. Of the total fatalities, 75 % occurred outside of the mapped hazard zones. Particularly dangerous places were campsites, cellars and basement flats, but many people died on the ground floor (37 %) or outside on the street (18 %). The elderly above 60 years of age (78 %) and those with mobility or cognitive impairments (16 %) were particularly vulnerable. No gender-specific differences in vulnerability were observed. Thus, the main causes for the exceptionally high number of fatalities were the extreme severity of the flood and its underestimation by the population and authorities, as well as inadequate early warning and evacuation. Consequently, public understanding of the particular danger posed by flash floods must be improved, as must the development and presentation of worst-case scenarios in hazard maps. Additionally, impact forecasting can significantly improve emergency management of such unprecedented floods. Specific recommendations for disaster management are (1) that in the event of such extreme flash floods, the warning messages must focus on saving human lives – i.e. those at risk must be advised to move to safe places, e.g. to the upper floors, instead of trying to save belongings – and (2) evacuations must be initiated in good time, especially where flooding of the ground floor with high water levels is to be expected, paying particular attention to the safety of the elderly and people with limited mobility.

Soil erosion threatens soil fertility and food security worldwide, with agriculture being both a cause and a victim. Vineyards are particularly at risk due to the often steep slopes and detrimental management practices such as fallow interlines and bare soil under the vines. Therefore, the search for alternative management practices becomes vital, and vegetation covers, including mosses, have the potential to reduce soil erosion. However, research on moss restoration as an erosion control method is still in its infancy, and this form of erosion control has never been applied in vineyards. It is thus unclear whether moss restoration can be implemented in vineyards. In this study, the restoration of mosses was investigated by applying artificially cultivated moss mats in a temperate vineyard. The effects of moss restoration on surface runoff and sediment discharge were examined compared to bare soil and cover crops using rainfall simulation experiments (45 mm h−1 for 30 min) with small-scale runoff plots at three measurement times during 1 year (April, June, and October). Mosses initially showed considerable desiccation in summer, whereupon their growth declined. In October, the mosses recovered and re-established themselves in the vineyard, showing a high level of resistance. Moss restoration significantly reduced surface runoff by 71.4 % and sediment discharge by 75.8 % compared with bare soils. While moss restoration reduced surface runoff slightly more and sediment discharge slightly less compared with cover crops (68.1 % and 87.7 %, respectively), these differences were not statistically significant. Sediment discharge varied seasonally for moss restoration, especially from April to June; this is most likely due to the decline in moss cover and the foliage of the vines in June, as concentrated canopy drip points form on the leaves and woody surfaces of the vines, increasing erosion. Overall, moss restoration proved to be an appropriate and low-maintenance alternative for erosion control, as it requires no mowing or application of herbicides. However, future research should address challenges such as preventing moss mats from drying out in summer; developing methods for large-scale application; and evaluating whether mosses significantly impact soil water content, potentially reducing water availability for vines.

Many cities seek carbon neutrality and are therefore interested in the sequestration potential of urban vegetation. However, the heterogeneous nature of urban vegetation and environmental conditions limits comprehensive measurement efforts, setting expectations for carbon cycle modelling. In this study, we examined the performance of three models – the Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg (JSBACH), the Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS), and the Surface Urban Energy and Water Balance Scheme (SUEWS) – in estimating carbon sequestration rates in both irrigated and non-irrigated lawns, park trees (Tilia cordata), and urban forests (Betula pendula) in Helsinki, Finland. The test data included observations of various environmental parameters and component fluxes such as soil moisture and temperature, sap flow, leaf area index, photosynthesis, soil respiration, and net ecosystem exchange. Our analysis revealed that these models effectively simulated seasonal and annual variations, as well as the impacts of weather events on carbon fluxes and related factors. However, the validation of the absolute level of modelled fluxes proved difficult due to differences in the scale of the observations and models, particularly for mature trees, and due to the fact that net ecosystem exchange measurements in urban areas include some anthropogenic emissions. Irrigation emerged as a key factor often improving carbon sequestration, while tree-covered areas demonstrated greater carbon sequestration rates compared to lawns on an annual scale. Notably, all models demonstrated similar mean net ecosystem exchange over the urban vegetation sector studied on an annual scale over the study period. However, compared to JSBACH, LPJ-GUESS exhibited higher carbon sequestration rates in tree-covered areas but lower rates in grassland-type areas. All models indicated notable year-to-year differences in annual sequestration rates, but since the same factors, such as temperature and soil moisture, affect processes both assimilating and releasing carbon, connecting the years of high or low carbon sequestration to single meteorological means failed. Overall, this research emphasizes the importance of integrating diverse vegetation types and the impacts of irrigation into urban carbon modelling efforts to inform sustainable urban planning and climate change mitigation strategies.

Coal seams in valley areas are shallow buried, and mining activities have a strong impact on the surface environment, so ecological restoration in this condition is very difficult. Strengthening the monitoring of ecological changes plays an important role in optimizing mining methods and ecological restoration. In this article, a valley area in the northern Shaanxi Province of China was selected as the research area, and a similar ecosystem around the study area was selected as the reference subject. The traditional remote sensing ecological index model was improved, and a new evaluation model was constructed based on the framework of Modified Remote Sensing Ecology index-Deviation from Reference Ecosystem Index-Ecological Restoration Quality Index (ERQI) to study the evolution of the environment in the study area from the perspective of the whole life cycle of mining activities. The results showed that ERQI values in the study area experienced an evolution process from high to low and then gradually increased, reflecting the impact of coal mine production and restoration activities on the environment, in which Burn Area Index and normalized difference vegetation index were more sensitive; after nearly 10 years of restoration, ERQI values in the study area still had a large gap with that of the reference area, some suggestions for improvement of ecological restoration were put forward. The research provided a quantitative approach to describe the evolution of the ecological environment and a scientific basis for the ecological restoration in the mining areas.

The organic geochemical and petrological analyses of calculated vitrinite reflectance of the Early Permian to Middle Triassic Formation section of the Sydney Basin in Australia have revealed the source for the widely distributed oil and gas shows in the basin. The coal formations of the Permian in the Sydney Basin have a higher hydrogen index with much higher TOC extracts than the non-coal formations of the Permian in the same basin. Some source-specific parameters attained from biomarkers, such as n-alkanes, regular isoprenoids, terpanes, diasteranes, and steranes, show that oil was generated and expelled mainly from organic matter derivatives of higher plants deposited in the oxic environment. The biomarkers associated with maturity, source, and aromatic hydrocarbon are mostly from coal core samples. However, extracts from non-coal samples have an organic geochemical signature, indicative of mixed terrestrial and prokaryotic organic matter deposited in a suboxic environment. Significantly, it is different from the coal extracts. Still, the molecular signature of some of the coal samples shows prokaryotic organic matter present in the extracts, indicating a thin section of possibly a calcareous lithology interbedded within the coal measure formation. Genetically, the coal extracts of the Permian in the Sydney Basin, Australia, provide a new insight into the generation and expulsion of oil from coal, which might be responsible for the widespread oil and gas shows in the basin. This raises the possibility of commercial oil accumulation in the early Permian coals to Middle Triassic sandstones, perhaps in the deeper part of the offshore basin.

Arid/semi-arid regions face water challenges much like the Arabian Peninsula, which is primarily caused by continuing shortages and growing activities of reclaimed land, as well as industrial and domestic activities. Consequently, identifying groundwater prospective zones (GWPZs) has become essential for securing water resources. The study aims to delineate and predict the best areas of groundwater prospection and abstraction by implementing the analytical hierarchy process-geographic information system (GIS) techniques in a rough terrain that occupies ∼70% of fractured hard rocks including ∼34% of the basaltic flow sheet of Wadi Marawani, Saudi Arabia. To investigate the combined impact of the model, 13 input thematic maps, including elevation, slope, curvature, depression, drainage density, Topographic Wetness Index, distance to river, Stream Power Index, Terrain Roughness Index, geology, lineaments, Normalized Difference Vegetation Index, and rainfall factors, were created, and employed in the model, which was subsequently merged through GIS techniques to reveal prospective zones. These maps are mainly derived from Shuttle Radar Topography Mission, Sentinel-1, Landsat, and Tropical Rainfall Measuring Mission. The output map is categorized as very low, low, moderate, high, or very high, and excellent occupying ∼7%. This promising zone is the result of the intersection of several criteria that control groundwater occurrences. The results were enhanced by implementing optical and radar remote sensing data, and thus, suitable recharge places for the future governance and abstraction of groundwater have been identified using GIS–AHP–multicriteria decision analysis methods. For validation, large numbers of well/spring locations that reached 415 are used in total. The efficiency of the model is estimated at 79.90% (area under curve) based on the receiver operating characteristic curve. Moreover, the Interferometry Synthetic Aperture Radar coherence change detection image validated the predicted model and revealed areas of no-coherence areas marked in brown matched to vegetated areas and excellent zones of GWPZs. The applied methodologies and findings of this study present significant insights for water resources planning and management to develop groundwater resources in similar regions worldwide.

Coal mining in ecologically fragile areas results in the failure of aquiclude layers and the loss of surface water bodies. Herein, research was conducted on the microbial solidification of cracked soils and the corresponding response of the ecological water table. A simulation of mining-induced cracked soils was performed via microbial solidification. The mechanical and hydrological properties of cracked soil samples repaired with different filling materials were compared via unconfined compressive strength and falling head permeability tests. Hydraulic-electric similarity modeling techniques were employed to evaluate the effectiveness of microbial solidification in the aquiclude layers. After low-temperature acclimation, Bacillus megaterium adapted to the geological environment of the study area, exhibiting a high viable cell density. When the cracked soil was filled with a 1:1 ratio of aeolian sand to clay particles, the microbially remediated soil demonstrated optimal mechanical and hydraulic properties. Hydraulic-electric similarity numerical simulations revealed that the ecological water table at the coalface remained within a reasonable range following microbial solidification, suggesting that microbial solidification achieved water-preserving coal mining. These findings provide a reference for restoring aquiclude layers damaged by coal mining.

Exploring the coupling relationship of “pattern–process–quality” is conducive to understanding the internal mechanism of habitat quality change, and is of great significance for the function maintenance and sustainable management of regional ecosystems. Existing studies mainly analyze the spatial-temporal evolution of habitat quality from the perspective of “pattern quality” and land use data. However, the variation in habitat quality is the result of many factors such as “pattern–process–quality” of the habitat. Therefore, it is necessary to consider these factors comprehensively when studying the change in habitat quality, so as to understand the change mechanism of habitat quality more comprehensively and deeply. This study takes Cambodia, a tropical monsoon climate region, as the research area, and uses land cover data from 2000 to 2022 as the data source. InVEST model is used to analyze the spatial-temporal evolution of habitat quality, and explore the relationship between habitat quality and land use, landscape pattern, and ecological process. The results show that (1) during 2000–2022, forest in Cambodia covered a wide range, showing a landscape pattern mainly distributed in the east and west. (2) The degree of fragmentation of impervious landscape pattern increased gradually from 2000 to 2022, indicating that it was seriously affected by human activities and natural factors, and with the increase in elevation and slope, the area of various types converted to impervious decreased. (3) During 2000–2022, high habitat quality areas were concentrated in Tonle SAP Lake in the east, southwest, and central part of Cambodia, while low habitat quality areas were concentrated in the central part. (4) Natural factors, socio-economic factors, policies, and regulations all have an impact on the change in land use pattern and habitat quality in Cambodia.

Due to the tight sandstone widespread development of nanoscale pore-throat systems, the microscopic pore-throat characteristics of tight reservoirs are the focus of research. Taking the main tight oil production province of the Ordos Basin in China as a case study, nuclear magnetic resonance (NMR), pressure-controlled mercury injection (PMI), scanning electron microscopy, and micro-computed tomography (μCT) are used to analyze the characteristics of four types of tight sandstones with different pore throats. Furthermore, the effects of pore throats on movable fluid, connectivity, and reservoir physical properties are analyzed. The results show that the pore throats of the four types of tight sandstones are obviously different, but they are all dominated by nanoscale pore-throat systems. From types I to IV, the pore types of the tight sandstone change from residual intergranular pores to the coexistence of feldspar dissolved pores and residual intergranular pores and then to the coexistence of residual intergranular pores and intergranular micropores. The T 2 NMR spectrum changes from a double peak to a single peak, the pore-throat connectivity revealed by μCT decreases from 83.8% for type I to 13.1% for type IV, the pore-throat volume ratio revealed by PMI decreases from 2.09 to 0.43, and the NMR movable fluid saturation decreases from 38.91 to 12.39%. Tight sandstone with larger pores and a uniform distribution has high movable fluid saturation and good pore-throat connectivity. Although the tight sandstone with dissolved pores and intergranular pores may have a medium porosity, the pore–throat connectivity deteriorates compared with high porosity sandstone. Large pore throats, which account for less than 15% of all pore throats, contribute more than 90% of the permeability, while pore throats less than 0.8 μm in diameter are major contributors to the reservoir space, and both the porosity and permeability decrease as the pore-throat diameter decreases.

We explore how atmospheric rivers (ARs) in a summer and winter case interact with the topography of the Amundsen Sea Embayment, West Antarctica, and deposit significant precipitation amounts. To do this we use results from three regional climate models (RCMs: MetUM, Polar-WRF, HCLIM) at a spatial resolution of 1 km. Estimates of snowfall associated with both events from all three RCM simulations compare well against observed snow height measurements over the Thwaites and Pine Island ice shelves. By contrast, snowfall estimates from ERA5 reanalysis for both events are severely underestimated (by 3–4 times) compared to the measurements. Outputs from the RCMs also show that the ARs may be associated with several millimetres of rain in both the summer and winter cases, although in the absence of in situ measurements of rainfall, this result cannot be directly verified. The RCM simulations suggest that rainfall during these events can fall directly as supercooled drizzle but also that rainfall is concentrated around steep terrain due to the interaction of ARs with complex orography. We also show that while the amount of MetUM-simulated snowfall was comparatively resolution-insensitive, the amount of rainfall simulated was not, with rainfall amounts over Thwaites Ice Shelf 4–16 times higher in 1 km simulations compared to 12 km simulations. Our work highlights that kilometre-scale models are useful tools to investigate the total precipitation amount and its partitioning into rain and snow over this globally important and climatically sensitive region, and it highlights the critical need for in situ observations of rainfall.

Accurately quantifying global mass changes at the Earth's surface is essential for understanding climate system dynamics and their evolution. Satellite gravimetry, as realized with the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions, is the only currently operative remote sensing technique that can track large-scale mass variations, making it a unique monitoring opportunity for various geoscientific disciplines. To facilitate easy accessibility of GRACE and GRACE-FO (GRACE/-FO in the following) results (also beyond the geodetic community), the Helmholtz Centre for Geosciences (GFZ) developed the Gravity Information Service (GravIS) portal (https://gravis.gfz.de, last access: 21 January 2025). This work aims to introduce the user-friendly mass anomaly products provided at GravIS that are specifically processed for hydrology, glaciology, and oceanography applications. These mass change data, available in both a gridded representation and as time series for predefined regions, are routinely updated when new monthly GRACE/-FO gravity field models become available. The associated GravIS web portal visualizes and describes the products, demonstrating their usefulness for various studies and applications in the geosciences. Together with GFZ's complementary information portal https://www.globalwaterstorage.info/ (last access: 21 January 2025), GravIS supports widening the dissemination of knowledge about satellite gravimetry in science and society and highlights the significance and contributions of the GRACE/-FO missions for understanding changes in the climate system. The GravIS products, divided into several data sets corresponding to their specific application, are available at https://doi.org/10.5880/GFZ.GRAVIS_06_L2B (Dahle and Murböck, 2019), https://doi.org/10.5880/COST-G.GRAVIS_01_L2B (Dahle and Murböck, 2020), https://doi.org/10.5880/GFZ.GRAVIS_06_L3_ICE (Sasgen et al., 2019), https://doi.org/10.5880/COST-G.GRAVIS.5880/GFZ.GRAVIS_01_L3_ICE (Sasgen et al., 2020), https://doi.org/10.5880/GFZ.GRAVIS_06_L3_TWS (Boergens et al., 2019), https://doi.org/10.5880/COST-G.GRAVIS_01_L3_TWS (Boergens et al., 2020a), https://doi.org/10.5880/GFZ.GRAVIS_06_L3_OBP (Dobslaw et al., 2019), and https://doi.org/10.5880/COST-G.GRAVIS_01_L3_OBP (Dobslaw et al., 2020a).

We present the first comprehensive multiyear global mapping of offshore lighting structures derived from low-light imaging satellite observations collected at night. The sensor is the day–night band (DNB) flown as part of the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS). The product merges two operational nighttime light products: VIIRS boat detection (VBD) data and VIIRS cloud-free nighttime light (VNL) data. The two products are spatially complementary, making it possible to fill gaps through a merger. Both product sets have an average DNB radiance layer, and the merger involves preserving the higher of the two average radiances. A wide range of lighting structures is present, i.e., fishing grounds, platforms, anchorages, gas flares, transit routes, and the glow surrounding bright lighting onshore. The richness of the numbers and types of offshore lighting structures can be traced back to the DNB spike detector at the core of the VBD algorithm. The VNL algorithm uses outlier removal to filter out biomass burning, an essential process for mapping electric lighting onshore. The outlier removal drops about 80 % of the offshore lighting detections. We expect that the new product will lead to an improved understanding of fishing grounds, offshore light pollution, and supply chain disruptions at anchorages, thereby aiding in the development of more sustainable and efficient practices. The global datasets are available at https://doi.org/10.25676/11124/179157 (Elvidge et al., 2024).

Abstract The performance of pavement and bridges on a stretch of 21.4 km of Calabar—Itu highway is the focus of this study. Within this 21.4 km section, the pavement structure has completely failed while the three bridges within this section are still in good structural health as there is no failure of both superstructure and foundation. Three groups of shale soils characterize this stretch; these are Ekenkpon Nkporo, and New Netim Marl. The materials were characterized by both geotechnical and geophysical methods at shallow and deep surface. The Ekenkpon and Nkporo classifies as organic silt and clay with high plasticity (OH) and Inorganic silt, (MH) respectively, while New Netim marl classify as lean clay (CL). Geotechnical shear strength properties determined by Direct shear tests for Ekenkpon indicate cohesion value’C, of 36.1 kN/m2, angle of shearing resistance of 36.8°, that of Nkporo shale with cohesion value as 36 kN/m2 and angle of internal friction as 3.6°. Based on the shear strength properties, Ekenkpon shale has a bearing capacity of 3902.95 kN/m2, Nkporo shale has a value of 667.02 kN/m2, and New Netim Marl with a value of 319.75 kN/m2. Within the load range of 50 kN/m2 to 500 kN/m2 the compressibility values for Nkporo are between 0.29 and 0.23 per MPa, while that of Ekenkpon shale for the same load range is between 0.78 and 1.50 per MPa, showing Ekenkpon shale is highly compressible than the Nkporo shale. Shallow seismic refraction survey involving both p and s-waves were also deployed to evaluate the quality of soils at some locations along this alignment. Results indicate the near the surface horizon which serves as the foundation for highway pavement is composed of soil materials that are highly permeable, dispersive, collapsible, easily eroded as indicated by low Slake Durability Index with values between 6.9 and 51.42%; properties which are all dependent on changes in water content. Whereas at depth, the same soil sequence but stable as permeability to water is very low, hence the stability of bridge foundations in them.

Abstract Borehole water plays a critical role in providing drinking water in Effurun, Delta State, Nigeria. However, concerns about potential contamination from both natural and anthropogenic sources necessitate regular groundwater quality assessments. This study evaluates the hydrochemical properties of borehole water to ensure public health safety and to understand the groundwater's suitability for consumption. The aim of this study is to assess the quality of borehole water in Effurun by analyzing major ions, trace metals, and other hydrochemical parameters, and to compare the findings with WHO and NSDWQ drinking water standards. Ten borehole water samples were collected from various locations across Effurun. Hydrochemical analyses were conducted to measure cations (calcium, magnesium, sodium, potassium), anions (chloride, bicarbonate, sulfate, nitrate), and trace metals (lead, copper, zinc, manganese). Statistical analysis and spatial mapping were employed to evaluate the distribution of ion concentrations and identify areas of concern. Calcium levels in the boreholes ranged from 29.95 mg/L to 64.50 mg/L, while magnesium levels were more consistent, ranging between 9.50 mg/L and 14.20 mg/L. Sodium and potassium showed moderate correlations with calcium. Chloride levels varied widely, indicating potential contamination from seawater intrusion or industrial discharge. Elevated sulfate and nitrate concentrations pointed to agricultural runoff. Trace metals, particularly lead, exceeded safety limits, with lead concentrations ranging from 0.092 mg/L to 0.127 mg/L, posing significant health risks. Spatial analysis revealed varying ion concentrations across Effurun, with higher calcium and magnesium levels near water bodies, suggesting local geology's influence. The central area exhibited moderate ion concentrations, while the southeastern region had the highest calcium levels, possibly due to geological formations rich in calcium or human activities. The study highlights diverse hydrochemical characteristics of Effurun's borehole water, with some areas showing contamination beyond acceptable limits. Regular monitoring is essential to ensure safe drinking water and address potential health risks. The findings stress the need for improved water resource management and contamination control. This study provides a comprehensive spatial analysis of groundwater quality in Effurun, identifying specific areas at risk of contamination and offering data-driven recommendations for public health and sustainable water management.

Abstract Sand mining using dredging technology from channel bars is a common technique worldwide. To minimize adverse effects of dredging, geo-engineering nature of the soil should be evaluated before mining. Therefore, the present study deals with the potential risks associated with dredging for mineral sand extraction by analyzing the engineering geological properties of the soil from the Brahmaputra River bar and the surrounding areas, Bangladesh. A detailed engineering geological analysis was conducted using field and laboratory testing methods, including Standard Penetration Tests (SPT), mineralogy, grain size distribution (GSD), California Bearing Ratio (CBR), and direct shear tests. The findings divulge that the soil in the study area is light gray, unconsolidated, moderately sorted, poorly graded, and classified as fine-to-medium silty sand. SPT-based liquefaction potential assessments suggest that the soils are highly susceptible to liquefaction, particularly during dredging or seismic events. The study also identifies the risk of localized slumping and soil instability, which exacerbated by micaceous and quartz-rich sands. The CBR results further classify the subgrade as weak to medium-strong, indicating risks of slumping, erosion, and instability. The non-cohesive granular soil in the area may liquefy or be susceptible to erosion, wave attack, bank slope failures, and seepage development during and after dredging as indicated from GSD and direct shear test results. Thus, proper safety precautions, including soil stabilization techniques, controlled dredging, and slope reinforcement, should be taken before dredging on such river bar to minimize risk. This research offers practical guidance for dredging companies to minimize risks and improve soil stability, contributing to safer and more sustainable river bar dredging operations worldwide.

Abstract Information on geomagnetic field intensity in the past is essential for understanding the behavior and mechanism of the geodynamo. A fundamental unresolved problem of relative paleointensity (RPI) estimations from marine sediments is that changes in the constituents of magnetic mineral assemblages may influence RPI estimations, called lithological contamination. A negative correlation between RPI and the ratio of anhysteretic remanent magnetization (ARM) susceptibility to saturation isothermal remanent magnetization (k ARM/SIRM), which is a proxy for the proportion of magnetofossils to detrital magnetic minerals, was previously reported from deep-sea sediments. This could be caused by lower RPI recording efficiency of the magnetofossil component than the detrital component. To elaborate further this issue, we have conducted a paleo- and rock magnetic study of a sediment core taken from the central north Pacific. RPI estimated from a slope in a diagram plotting a pair of natural remanent magnetization (NRM) and ARM at each alternating-field demagnetization step (NRM-ARM demagnetization diagram) has a negative correlation with k ARM/SIRM. Principal component analysis of first-order reversal curve diagrams indicates a downcore increase of the magnetofossil proportion with increased k ARM/SIRM. These results reinforce the lower RPI recording efficiency of magnetofossils. In this core, the magnetic coercivity ranges of the magnetofossil and detrital components overlap, which produces a linear NRM-ARM demagnetization diagram. This hinders a possibility of obtaining uncontaminated RPI from a coercivity window representing the magnetofossils or detrital magnetic components, which was tried by some previous studies. A linear NRM-ARM demagnetization diagram, which was sometimes used as a criterion of reliable RPI estimations, does not necessarily mean the absence of lithological contamination to the RPI. In sediments with changing proportion of magnetofossils, normalization with IRM may work better than ARM. Graphical Abstract

Abstract Many studies have estimated crustal deformation from observed geodetic data. So far, because most studies have applied a smoothness constraint, which includes the assumption of local uniformity of a strain-rate field, localized strain rates near fault zones have tended to be underestimated when we invert spatially sporadic GNSS data. To overcome this difficulty, we introduce sparse modeling into the estimation of a strain-rate field. Specifically, we impose a sparsity constraint as well as the smoothness constraint on strain rates as prior information, which are expressed by the L1-norm and the L2-norm of the second-order derivative of the velocity field, respectively. To investigate the validity and limitation of the proposed method, we conduct synthetic tests, in which we consider an anti-plane strain problem due to a steady slip on a buried strike-slip fault. As a result, we find: (1) regardless of the locking depth of the fault, the proposed method reproduces localized strain rates near the fault with almost equal or better accuracy than the L2 regularization method (i.e., only the smoothness constraint); (2) the advantage of the proposed method over the L2 regularization method is clearer when data coverage is worse (i.e., when fewer observation points are available); and (3) the proposed method can be applied when observation errors are small. Next, we apply the proposed method to the GNSS data across the Arima-Takatsuki fault zone, which is one of the most active strike-slip faults in Japan. As a result, the proposed method estimates about $$1.0\times {10}^{-8}$$ 1.0 × 10 - 8 /yr faster strain rates near the fault zone than the L2 regularization method, which corresponds to a 20–30% greater strain-rate concentration. The faster strain rates result in the estimation of a shallower locking depth: 11 km by the proposed method, compared to 17 km by the L2 regularization method. The former is closer to the depth of D90, 12–14 km, above which 90% of earthquakes occur. Graphical Abstract

Abstract We conduct a series of numerical experiments of thermal convection of compressible fluids with temperature-dependent viscosity, in order to study how the adiabatic compression and model geometries affect the mantle convection on super-Earths. A two-dimensional basally heated convection is considered under the truncated anelastic liquid approximation (TALA), either in a rectangular box or in a cylindrical annulus. We varied the magnitude of adiabatic heating and the Rayleigh number as well as the depth profile of thermodynamic properties (thermal expansivity and reference density) in accordance with the planetary sizes. From our calculations by varying the planetary sizes up to 10 times the Earth’s mass, we confirmed that the adiabatic compression affects the thermal convection more strongly for larger planets. The activity of hot plumes originating from the core–mantle boundary is significantly suppressed in the terrestrial planets whose mass is larger than the Earth’s by a factor of about 3 regardless of the model geometries. We also developed scaling relationships between the vigor of thermal convection and the planetary mass by appropriately incorporating the effect of adiabatic compression into those of Boussinesq (or incompressible) cases. Our scaling relationships suggest that the stress level in the top cold thermal boundary layers is almost independent of the planetary mass, which may further imply that the emergence of plate tectonics is not likely to be enhanced for massive terrestrial planets whose composition is similar to the Earth’s. Graphical Abstract

Abstract Previous drilling and coring efforts have confirmed the presence of methane hydrates in the deepwater Makassar Strait of Indonesia. The strait, separated into the North Makassar Basin and South Makassar Basin, is situated on the thinned Eurasian continental crust that began to rift during the Middle Eocene. While past methane hydrates studies have focused on the northern basin, the southern region lacks equivalent investigation. This research employs legacy multi-channel seismic reflection and well logs data to decipher the methane hydrate systems and associated free methane in the South Makassar Basin. Identified through the interpretation of bottom simulating reflectors (BSRs), seafloor topography, and structural features on seismic reflection profiles are five primary play types: polygonal faults type, slope type, buried fold type, buried carbonate mound type, and sediment waves type. The distinctive characteristics of BSRs in this region can be summarized as follows: (1) predominantly located beneath topographic highs and basin depocenter, (2) typically displaying a series of high-amplitude dipping reflectors beneath BSRs, (3) the distribution of BSRs is not always continuous and is not always parallel to that of the seafloor, and (4) the presence of blanking reflection above BSRs is variable. These features suggest methane hydrate accumulation preferentially occurs beneath structural highs and in basin depocenters, likely due to the upward and lateral migration of buoyant, methane-rich fluids. Through the analysis of seismic amplitude distribution and reflection strength in relation to BSR depth, hydrocarbon distribution is categorized into methane-hydrate reservoirs above BSRs and free methane reservoirs below BSRs. A first-order estimation of methane resources via petrophysical approach and Monte Carlo simulation suggests approximately 105 trillion cubic feet (TCF) of methane resources.

Abstract This study investigates the effects of non-zero IMF B y on the magnetotail B y and fast earthward ion convection (V ⊥ > 200 km/s, "⊥" indicates perpendicular to the magnetic field) in the near-lunar magnetotail plasma sheet using the plasma parameters and magnetic field detected by the ARTEMIS (Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon’s Interaction with the Sun) P1 satellite during the period 2011–2022. We find that the magnetotail B y with in the same direction as IMF B y dominates the entire region. The IMF B y influence is hemisphere-independent, but shows a dusk-dawn asymmetry with the IMF B y effect being weaker in the premidnight region than in the postmidnight region. We also find that the IMF B y influence on earthward fast convection results in an interhemispheric flow asymmetry and it is highly correlated with the direction of magnetotail B y. The statistical results indicate that occasionally localized dynamics can have a significant effect on magnetotail B y and V ⊥.

Abstract The shape of gravity anomalies changes due to the disruption of geological bodies’ continuity by fault structures, and their planar contour line characteristics are an important basis for dividing fault structures. However, the traditional potential field boundary identification method has limited ability to detect the boundaries of buried deep geological bodies. Therefore, geophysicists at home and abroad have proposed various new techniques for potential field boundary identification. These techniques aim to effectively and rapidly extract or enhance weak anomaly information about geological bodies’ boundaries. They also aim to delineate the distribution range of field sources. This paper systematically analyzes the principles of various gravity potential field boundary identification methods. It also uses various methods to process and interpret the Bouguer gravity anomalies in the Anza Basin of Kenya. Additionally, it determines the fault system in the basin and carries out structural zoning. The results of the processing of various gravity boundary identification methods with the gravity data in the study area show that a gravity gradient zone is developed in the Anza Basin, where the Bouguer gravity anomalies are all negative and exhibit a large variation range, overall showing a high-southwest and low-northeast trend. The analysis of residual gravity anomaly yields results indicating that the local structure of the study area has obvious structural pattern of the “east-west zone and north-south block”. The study area exhibits developed faults, which can be mainly categorized into two sets with northwest direction and northeast direction orientations. Small-scale northeast-direction faults cut off larger-scale northwest-direction faults. Six tectonic zones were recognized in combination with the gravity anomalies and seismic data in the study area, which include eastern depression, southern uplift, central bulge, western depression, northern slope and western uplift.

Abstract A displaced segment of the Late Triassic–Late Jurassic Greater Adriatic margin of the Neotethy Ocean was investigated in NE Hungary. In this area, the Mesozoic basement is largely covered by the Palaeogene—Miocene infill of the North Hungarian Palaeogene Basin and the Pannonian Basin. Micropaleontological, sedimentological and structural investigation of more than thirty wells resulted in the detailed characterisation and 3D depositional model of the area, which may have formed in the eastern continuation of the Slovenian Basin or in a similar sub-basin. The sedimentation in its Bajocian–early Callovian extensional half-grabens was characterised by pelagic limestones followed by dark shales with sandstone intercalations. Mass-flow deposits derived from both the footwalls of graben-bounding normal faults and the Adriatic Carbonate Platform were frequent. The most basin-ward segment of the latter one was penetrated by the south-westernmost well of the area. Both the Middle Jurassic extension of the formerly extended continental crust and the lower plate source of the sediments have great importance, while they change the tectonic interpretation of the basins. In the overlying Tarna olistostrome sedimentation lasted at least until the Tithonian, as indicated by nannofossils. This is the oldest possible age for the overthrusting of the ophiolite nappe over this segment of the Greater Adriatic continental margin. The now eroded ophiolite nappe is underlain by the Darnóhegy Mélange, a typical sub-ophiolitic mélange, which was formed further to the south-east during the Callovian–Oxfordian, at an earlier, intraoceanic stage of the Neotethyan subduction.