bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards operational impact based flood forecasting in Norway
Authors: Engeland Kolbjorn , Hegdahl Trine Jahr Hegdahl , Jjunju Emmanuel , Sandboe Kamilla Skåre
Published: March 2024

Impact based forecasting is identified as a major challenge for hydrometeorological services by WMO. Impact based flood forecasting aims at closing the gap from forecasting how high the streamflow might be in the coming days to forecasting what the high flows might do. The target audience for impact-based flood forecasts can be both the population at large and the authorities responsible for civil protection and emergency management at national, regional, and local levels.Since 1989 The Norwegian Water Resources and Energy Directorate (NVE) has been running the national services for forecasting floods and issuing warnings for regions and municipalities. Precipitation-runoff models for almost 160 catchments distributed all over Norway are used to forecast streamflow. Flood warnings are then mainly issued based on predefined thresholds for streamflow (mean flood, 5- and 50 years floods). The warnings mention typical impacts of the expected floods but not specific impacts.NVE aims to provide impact-based flood forecasts for Norway and has started a 4-year pilot for four selected catchments in Norway to assess the information, models and tools needed to achieve this aim. This presentation will present the approaches selected and discuss their challenges.The model chain used to assess impacts needs to represent the relevant processes. In a first step we focus on riverine floodings. A first challenge is that the hydrological models need to provide forecasts where the flood might have an impact, which signifies that the hydrological models will be applied in ungauged locations. Subsequently, hydraulic models can be used to estimate water levels and depths in susceptible areas. We evaluate an approach where the models are configured to sub-reaches of the rivers were the up- and downstream boundary conditions are well defined and forecasted streamflow at selected points is used as input. The hydrologic model can be used to establish an archive of flood levels and or depths to reduce computing time. This approach is challenging when downstream boundary conditions are dynamic, e.g., close to sea with tidal influence or inland lakes where the water level peaks later than discharge in the upstream rivers. The water levels and depths are subsequently used to estimate impacts based on the buildings and infrastructure potentially affected by the flood. Here we can use the type of building (storage, residential, school etc) type of road (municipality, regional or national road) to assess impact. An important challenge here is how to weight and aggregate potential impacts.
Archean continental crust formed by melting mafic cumulates
Authors: Smit Matthijs , Musiyachenko Kira , Goumans Jeroen
Published: March 2024

Large swaths of juvenile crust with tonalite-trondhjemite-granodiorite (TTG) composition were added to the continental crust from about 3.5 billion years ago. Although TTG magmatism marked a pivotal step in early crustal growth and cratonisation, the petrogenetic processes, tectonic setting and sources of TTGs are not well known. Part of this issue is the general difficulty in disentangling the chemical effects of fractional crystallization and partial melting, which impedes constraining primitive melt compositions and, by extension, investigating source-rock lithology and composition. To investigate these aspects, we assessed the composition and petrogenesis of Archaean TTGs using high field-strength elements that are fluid immobile, uniformly incompatible, but differently compatible between various residual minerals. The Nb concentrations and Ti anomalies of TTGs show the overwhelming effects of amphibole and plagioclase fractionation and permit constraints on the composition of primary TTGs. The latter are relatively incompatible element-poor and characterised by variably high La/Sm, Sm/Yb and Sr/Y, and positive Eu anomalies. Differences in these parameters do not represent differences in melting depth, but instead indicate differences in the degree of melting and fractional crystallisation. Primary TTGs formed by the melting of rutile- and garnet-bearing plagioclase-cumulate rocks that resided in the roots of mafic proto-continents. The partial melting of these rocks likely was part of a causal chain that linked TTG magmatism to the formation of sanukitoids and K-rich granites. These processes explain the growth and differentiation of the Archean continental crust, without requiring external forcing such as meteorite impact or the start of global plate tectonics.
Spatial probability of vent opening at the active central volcanoes of São Miguel (Azores)
Authors: Aguiar Simone , Sandri Laura , Pimentel Adriano , Oliveira Sérgio , Pacheco José
Published: March 2024

Forecasting the location of future volcanic eruptions is one of the most critical and challenging issues when assessing volcanic hazard. A long-term hazard assessment approach based on past eruptive behaviour is of utmost importance for dormant or low-activity volcanoes, on which sound land-use policies and risk mitigation plans should be based.São Miguel Island in the Azores Archipelago hosts three active central volcanoes (Sete Cidades, Fogo, and Furnas) that produced a large variety of eruptions in the last millennia and even in historical times, including trachytic explosive and effusive events and basaltic flank eruptions. Although these volcanoes are currently in a repose period, the likelihood of future eruptions should not be neglected.  This study focuses on the estimation of the spatial probability of vent opening at the Sete Cidades, Fogo, and Furnas volcanoes separately, using the kernel method. Here, we used the location of past basaltic and trachytic emission centres, in the form of vents or fissures, of each volcano, to explore different kernel functions (Gaussian, Cauchy, Exponential, and Uniform) and calculate the best degree of clustering of vents given by a smoothing parameter (h). This approach was applied to each volcano by considering (1) basaltic and trachytic emission centres (fissures and/or vents) and (2) only trachytic emission centres (vents). This allowed us to estimate the pair (kernel function and h-value) that best fits the empirical cumulative distribution function of the minimum distance between emission centres and compute the final vent opening probability maps conditional to an eruption (or susceptibility maps).For Sete Cidades, the results show that when considering basaltic and trachytic emission centres together, the southeast and west flanks of the volcano have a higher likelihood of hosting a new vent; however, when considering trachytic vents alone, the higher probability is at the west flank and southern sector of the caldera. The susceptibility map generated using Fogo’s basaltic and trachytic emission centres indicates a higher likelihood of hosting a new vent at the northwest flank of the volcano and southeast sector of the caldera. When only trachytic vents are considered, the southeastern sector of the caldera is more likely to host a new vent. For Furnas volcano, the results show that the northwestern part of the caldera has a higher likelihood of hosting a future basaltic or trachytic vent.
Advancements in COSP Lidar Simulator Development for Aeolus Satellite Instrument and Future Applications for Earth Care
Authors: Roussel Marie-Laure , Chepfer Hélène , Chomette Olivier , Bonazzola Marine
Published: March 2024

The Aeolus mission,  conducted by the European Space Agency (ESA), relies on lidar technology to measure global wind profiles and observe Earth's atmosphere, and in particular clouds that will be the subject of special attention with the incoming Earth Care mission. In future climate predictions generated through climate models, clouds represent the greatest source of uncertainty. Therefore, it is crucial to study them, especially within the atmospheric column, as their vertical distribution has a radiative impact which is poorly known. Active lidar remote sensing technology onboard satellites is a valuable way of conducting measurements accross the atmosphere. However, cloud comparison between observational data and models is challenging due to differences in their definitions. To address this issue, a simulator is employed to model cloud-specific features as they would appear to a given instrument if it were flying over the modeled Earth.This research initiative enhances the functionalities of the existing CFMIP Observation Simulator Package (COSP) (Bodas Salcedo, 2011). Our developments rest on the advancements achieved in adapting COSP for various satellite instruments in the past (Chepfer, 2006 & 2008) and its improvements over the years (Swales, 2018 - Bonazzola, 2023). The ongoing work focuses on refining the specifities of the current simulator to meet the unique requirements of the lidar of the Aeolus satellite and preparing thoses of ATLID onboard Earth Care satellite.The success of this development is optimistic for the future creation of the simulator of the lidar of the Earth Care satellite that may be launched this year, showing the adaptability and versatility of this tool. Ultimately, these advancements contribute to the broader scientific community by providing a sophisticated tool for the analysis of satellite data and the validation of model predictions across various satellite missions (Cesana, 2013).
Free surface methods applied to global scale numerical geodynamic models
Authors: Gray Timothy , Gerya Taras , Tackley Paul
Published: March 2024

The study of coupled Earth systems, and in particular the coupled interactions between the lithosphere, atmosphere, and biosphere, have received greater attention in recent years (Gerya et al. 2020). Interactions between these systems occur primarily at the surface, and are driven on the large scale by topographic and bathymetric evolution controlled by deep mantle processes. However, due to the large difference in length scales between the mantle and the surface, it is difficult to capture topographic evolution to a high degree of accuracy in existing global mantle convection models including a free surface boundary condition.Global mantle convection models incorporating a free surface often employ a marker-in-cell technique with a layer of “sticky air” (i.e. material with the density of the air and sufficiently low viscosity, which is still much higher than that of real air) to characterise the surface. However, accurate topographic evolution using this method requires a high density of markers near the surface. This need for additional computational resources motivates alternative methods of tracking the interface between the air and rock layers, as is done frequently in existing multiphase fluid flow codes. We demonstrate the implementation of two such methods of modelling the surface. The first is a Lagrangian marker chain (or mesh in 3D models) which, when combined with an appropriate remeshing procedure, directly tracks the rock-air interface. The second is a volume of fluid approach adapted from the open source code gVOF using the unsplit volume of fluid library gVOF (López & Hernández, 2022).We demonstrate toy models and benchmarks (based on those in Crameri, 2012) comparing the Lagrangian marker method and the volume of fluid methods as implemented in the global scale mantle convection code StagYY (Tackley, 2008). Models of global scale topography and evolution produced using StagYY may then be used as a tool for further studies on the coupling of mantle dynamics with modelling of the landscape, and the evolution of the atmosphere and biosphere. Initial applications include modelling hypsometric curves from global scale numerical models, and the tracking of sea level changes over time.
Rapid Computation of Physics-Based Ground Motions in the Spectral Domain using Neural Networks
Authors: Ramadan Fatme , Fry Bill , Nissen-Meyer Tarje
Published: March 2024

Physics-based simulations of earthquake ground motions prove invaluable, particularly in regions where strong ground motion recordings remain scarce. However, the computational demands associated with these simulations limit their applicability in tasks that necessitate large-scale computations of a wide range of possible earthquake scenarios, such as those required in physics-based probabilistic seismic hazard analyses. To address this challenge, we propose a neural-network approach that enables the rapid computation of earthquake ground motions in the spectral domain, alleviating a significant portion of the computational burden. To illustrate our approach, we generate a database of ground motion simulations in the San Francisco Bay Area using AxiSEM3D, a 3D seismic wave simulator. The database includes 30 double-couple sources with varying depths and horizontal locations. Our simulations explicitly incorporate the effects of topography and viscoelastic attenuation and are accurate up to frequencies of 0.5 Hz. Preliminary results demonstrate that the trained neural network almost instantaneously produces estimates of peak ground displacements as well as displacement waveforms in the spectral domain that align closely with those obtained from the wave propagation simulations. Our approach also extends to predicting ground motions for ‘unsimulated’ source locations, ultimately providing a comprehensive resolution of the source space in our chosen physical domain. This advancement paves the way for a cost-effective simulation of numerous seismic sources, and enhances the feasibility of physics-based probabilistic seismic hazard analyses. 
Large-scale reservoir modeling of the Vendenheim geothermal site (France)
Authors: Abreu Torres Javier , Hutka Gergo , Cacace Mauro , Blöcher Guido , Magnenet Vincent , Schmittbuhl Jean
Published: March 2024

During the Vendenheim deep geothermal project (Strasbourg Eurometropole, France), large induced seismic events led to the arrest of the project. Two important features of the induced seismicity were unexpected : the large distance to the wells of a cluster of seismic events (4-5km) and the occurrence of the largest event Mlv3.9 at the bottom of the wells, six months after shut-in. To better understand the mechanisms of seismicity, we develop within the framework of the DT-GEO project (Horizon Europe) a large-scale model (8kmx8kmx8km) of the area. We aim at performing in-silico experimentation to reproduce the geophysical responses of the geothermal reservoir with different geological geometries, different geomechanical properties and constrained with a variety of crustal stress conditions and variety of the external forcing representing the anthropogenic control. The model is based on the MOOSE/GOLEM framework (finite element approach) and integrate the public regional geological model GEORG that includes major lithologies and large-scale faults of the area. We will present the preliminary of coarse-grained simulations of the natural fluid circulation and fluid injections.
Dynamic Mode Decomposition enables decoding dominant spatiotemporal structures in global scale hydrological datasets
Authors: Libero Giulia , Tartakovsky Daniel M. , Ciriello Valentina
Published: March 2024

As climate change and human activities impact water availability worldwide, a better understanding of large-scale hydrologic phenomena is crucial to identify and design appropriate strategies for adaptation and mitigation. While decoding the interactions and evolution of the climate, human activities, and the water cycle can ease the assessment and forecasting of water resource availability, the complexity, and the computational demand limit the feasibility of these analyses on a global scale. Data-driven techniques are often used to gain physical insights in global hydrological phenomena and build efficient and computationally efficient models for future state prediction. One such technique, dynamic mode decomposition (DMD), enables one to capture the hidden information embedded in large hydrological datasets. This data-driven and equation-free technique is suitable for identifying spatiotemporal features of both observational and simulated data. DMD performs a low-dimensional spectral decomposition of the data to obtain a reduced-order model of the system behavior directly from temporal snapshots. DMD provides low-cost reconstructions and predictions of the observed variable, and its structure contains information about the temporal and spatial patterns of the system evolution. It provides a set of spatial modes whose contribution evolves in time according to a specific time dynamic which defines the frequency, the growth rate, and a related amplitude. Trend and seasonal variations are identified, and a physically meaningful interpretation are sought for the most important modes. We test the ability of a suite of different DMD algorithms to model and interpret the 20-year-long series of monthly total water storage anomalies provided by the Gravity Recovery and Climate Experiment (GRACE) satellite missions. The scope is twofold: learn directly from satellite observations and build efficient DMD-based models to ease forecasts and reconstructions, and at the same time, unveil the system’s leading order behavior and derive insights on Earth’s water cycle evolution.
Ground-based scanning Ka-band cloud radar observations for validation of EarthCARE Cloud Profiling Radar (CPR)
Authors: Ohigashi Tadayasu , Misumi Ryohei
Published: March 2024

The National Research Institute for Earth Science and Disaster Resilience owns five scanning Ka-band cloud radars. Using these radars, we are planning to validate the cloud profiling radar (CPR) of the EarthCARE satellite. The EarthCARE CPR only observes along the line directly under the satellite path and has a return period of about 25 days. Therefore, we will facilitate the comparison by collecting data from what we can consider to be the similar region as the EarthCARE path. Statistical validation will be performed by creating a Contoured Frequency by Altitude/Temperature Diagram (CFAD/CFTD) and comparing the distributions. Both case and relatively long-term comparisons are possible. On the other hand, although the opportunity is rare, it is possible to compare the vertical profiles at the intersection with the vertical (RHI) observations of the ground-based radar if the EarthCARE path comes within the range of the ground-based cloud radar with the observation range of 30 km. Three-dimensional observations using Plan Position Indicator (PPI) scans can be used to generate data on the Cartesian grid (CAPPI data). From this CAPPI data, it is possible to create a vertical cross section along the path of the EarthCARE satellite. Because of the limited number of elevation angles, the comparison is relatively coarse in the vertical direction. Since this observation is not done in the vertical direction, only radar reflectivity is used for comparison, not Doppler velocity. Other methods of verifying liquid water contents using cloud radar and microwave radiometer are also under consideration.
Impacts of melting glaciers and snowpacks in High Mountain Asia on downstream water and food security 
Authors: Biemans Hester , Lutz Arthur , Smolenaars Wouter , Jamil Khalid , Ludwig Fulco , Dhaubanjar Sanita , Immerzeel Walter
Published: March 2024

The high mountains of Asia store large volumes of water in their glaciers and snowpacks. Twelve large river basins, fed with meltwater from these mountains, are home to almost 2 billion people. In their floodplains, a significant fraction of the global food is produced (34% and 23% of the global rice and wheat production respectively). This makes the snow and ice in the High Mountains of Asia a very important water reserve on which both water- and food security for a huge population depend.However, the water supply from the mountains faces many threats. Glaciers and snowpacks are melting at unprecedented rates, and large parts of these reserves are likely to disappear by the end of the 21st century. At the same time, the dependence of downstream populations on mountain water resources is increasing, mainly due to increasing water needs, continuing groundwater depletion and changes in (monsoon) precipitation.Agriculture in the predominantly irrigated floodplains in Asia is very intensive, with often 2 or even 3 crops grown per year. In some of these agricultural areas, irrigation water supply is largely depending on the seasonal availability of meltwater. Any changes in meltwater supply could therefore have large impacts on the crop production, but science has only just started understanding the impacts of melting glaciers and snowpacks on food and water security of downstream populations.In this presentation we will look back on our recent work in which we quantified the current en future dependence of downstream crop production on water from the mountains in the Indus and Ganges basins. We also describe remaining challenges, and look ahead to the upcoming (ERC) 3POLE2SEA project,  that aims to quantify these upstream-downstream linkages in all twelve river basins river basins originating from the High Mountains of Asia. We expect that the 12 river basins have very different upstream-downstream dependencies, resulting in different current and future risks for water and food security, and therefore need different responses for effective adaptation. We explain how our research can contribute to making agriculture in one of the largest food producing areas in the world more resilient to changes in the mountains.
Using long-term remote sensing series to upscale the vegetation shifts along elevation in the GLORIA network Italian peaks
Authors: Vuerich Marco , Boscutti Francesco , Mosanghini Davide , Trotta Giacomo ,   GLORIA Italian Network team
Published: March 2024

Plant species and communities’ distribution are remarkably affected by the climate change, particularly in arctic and alpine biomes. In alpine ecosystems, species and communities are shifting upwards due to the temperature increase, seeking for the optimum growth conditions. As a prominent effect, a progressive increase of vegetation cover is leading an alpine greening, with important consequences for the overall plant diversity. Nonetheless, little is known about how this trend may produce different effects along elevation gradients. Innovative upscaling approaches able to link field monitoring evidence to remote sensing data represent a promising tool to get new insights into the ecological mechanisms involved in these changes, and to produce reliable projections over time. This study aimed at parsing the long-term trends of remote sensing-derived vegetation indices in five GLORIA (Global Observation Research Initiative in Alpine Environments) network target regions, located across the Italian Alps and Apennines. Normalized Difference Vegetation Index (NDVI) was calculated for each growing season (June-September) in the period 1985-2022, using Landsat 5 and 8 multispectral satellite images of each mountain summit. Linear mixed-effects models were used to analyze the relationships between NDVI, time and climate variables, in different elevation belts. NDVI linearly increased over the last 37 years, but with significant higher increase rates and values at the treeline, lower alpine and alpine zones, compared to the upper alpine, subnival and nival belts. Moreover, NDVI was significantly affected by temperature at lower altitudes, with a significant interaction with rain precipitations, while climate variables were not determinant at high elevations. These results provided further evidence of the ongoing alpine greening and showed that vegetation at the treeline is responding faster than the other communities to a warmer and drier climate. Therefore, future scenarios depicting the fate of alpine plant community communities should not neglect for the interplay of temperature and precipitation regimes. Our finding opens future perspectives on the interpretation of GLORIA field evidence, in a continental upscaling perspective.
On multi technique precise orbit determination for SWOT with respect to altimetry applications.
Authors: Reinhold Anton , Schreiner Patrick , Schöne Tilo
Published: March 2024

SWOT (Surface Water and Ocean Topography) is a recently launched international satellite mission developed in close collaboration between CNES and NASA space agencies aimed to reach a new level of accuracy in observing global water systems of the Earth. In order to meet the high accuracy requirements of the mission most precise determined orbits are crucial. Therefore we generate orbits using dynamic Precise Orbit Determination (POD) with multiple techniques, i.e. DORIS, GPS and SLR with the aim of generating a highly precise orbit with minimal residual error. For this purpose, single technique orbits are generated based on DORIS and GPS only, using SLR for validation only. For quality analysis we evaluate the estimated parameters of the dynamic POD and perform orbit comparisons to external orbit solutions. Subsequently, to reduce technique-specific effects of the dynamic modeling, we generate a combined orbit solution based on DORIS and GPS, and estimate the reference points of the observation techniques on the satellite to examine the calibration by the manufacturer. Based on the generated orbit solutions altimetry evaluation such as cross-over point analysis is made and discussed.
Developing machine learning algorithms to quantify carbon export fluxes in the ocean
Authors: González-González Beatriz , Villa-Alfageme María , Abascal-Ruiz Unai , Hurtado-Bermúdez Santiago-José
Published: March 2024

Quantifying the ocean carbon export and sequestration is essential to understand not only the marine carbon cycle but also the impact of the biological pump (BP) on global carbon cycle. The BP includes the different mechanisms by which atmospheric carbon is transferred from the surface to the deep ocean in a process started by the carbon synthetization of phytoplankton and followed by the formation and sinking of the marine snow, enabling the storage of carbon for long periods of time. Particulate organic carbon (POC) downward flux is a key and necessary parameter to characterize the BP and the ocean carbon cycle models.In order to estimate POC flux, radioactive pairs (238U-234Th or 210Pb-210Po) disequilibrium and sediment traps are robust and accurate methods; however, they generally present low spatial-temporal resolution. In situ optical observations have shown a big potential to generate a wide database of POC fluxes.Artificial intelligence (AI) and machine learning (ML) algorithms have already shown their potential in the last years to improve the estimations of oceanic POC concentration. It can be obtained as a satellite-derived product using colour remote sensing data, as POC is correlated with optical properties and water components (suspended particulate matter and chlorophyll-a). In contrast, ML have just only recently started to be used to evaluate POC export fluxes, partly because the lack of consistent and extensive datasets combining POC fluxes and ancillary parameters.Here, we review the state of art of the use of ML techniques for POC concentration predictions as the cornerstone for estimations of POC export fluxes. The potential of ML methodologies to generate global reconstructions of particle fluxes in the ocean, using the current available POC flux databases, will be discussed and described. We will finally include general guidelines to analyse POC export evaluations using ML and comprehensive databases.
A conceptual approach for deciphering mega-activity of debris flow fans and polygenetic fans for climate change anticipation
Authors: Gewalt Philipp , Krautblatter Michael
Published: March 2024

Debris flows are amongst the most dangerous geomorphic processes world-wide. In alpine environments, settlements and infrastructure are commonly located on debris flow fans. An over-proportional increase in debris flow activity has been shown to occur in response to climate warming under transport-limited conditions. Enhanced debris flow activity might not only affect transport volumes on existing fans. It could trigger a phase shift from regular debris flow activity to mega-activity leading to the generation of outsized fans. However, sediment fan formation during phases of exceptionally high debris flow activity remains largely unexplored: While more than 65 outsized sediment fans have been identified throughout the European Alps, only for three of them detailed sub-surface information exists. Although outsized-fan activity may provide invaluable information on the “things to come” in the next decades, the potential of outsized fans as analogues for future debris flow activity is so far unknown. To enhance our understanding of the magnitude, style, and landform-building potential of future debris flow activity, this research project investigates the following research question: What can current and past mega-activity on alpine debris flow fans teach us about future debris flow activity? We will investigate the spatio-temporal patterns of debris flow activity on a small, a medium, and an outsized alpine debris flow fan over decadal, centennial, and millennial timescales. On the small spatio-temporal scales, we will use geomorphic mapping, aerial photography, dendrochronologic dating, and digital elevation model differencing to investigate links between decadal climate change and debris flow activity. On the larger scales, we will combine several methods of near surface geophysics to derive the subsurface architecture of the sediment fans and thus gain insights into their formation history. We will use this information to calibrate a landscape evolution model of outsized fan formation to test the plausibility of the inferred formation history and ensure transferability of the results. This research project systematically deciphers the magnitude and outsized fan building potential of massively changing debris flow activity in the past to anticipate phase shifts in the foreseeable future.Key Words: Debris flow, polygenetic sediment fan architecture, climate change, outsized fan, geophysical tomography
Towards a community platform for paleoclimate data and temperature gradients over the last 540 million years 
Authors: Steinig Sebastian , Johnson Helen , Robinson Stuart , Valdes Paul J. , Lunt Daniel J.
Published: March 2024

Earth’s climate shows a remarkable variability on geological timescales, ranging from widespread glaciation to ice-free greenhouse conditions over the course of the Phanerozoic, i.e. the last 540 million years. Earth system modelling allows us to better understand and constrain the drivers of these changes and provides valuable reference data for other paleoclimate disciplines (e.g., chemistry, geology, hydrology). However, the sheer volume and complexity of these datasets often prevents direct access and use by non-modellers, limiting their benefits for large parts of our community.We present the online platform “climatearchive.org” to break down these barriers and provide intuitive access to paleoclimate data for everyone. More than 100 global coupled climate model simulations covering the entire Phanerozoic at the stage level build the backbone of the web application. Key climate variables (e.g. temperature, precipitation, vegetation and circulation) are displayed on a virtual globe in an intuitive three-dimensional environment and on a continuous time axis throughout the Phanerozoic. The software runs in any web browser — including smartphones — and promotes visual data exploration, streamlines model-data comparisons, and supports public outreach efforts. We discuss the current proof of concept and outline the future integration of new sources of model and geochemical proxy data to streamline and advance interdisciplinary paleoclimate research.We also present ongoing efforts for an integrated model-data synthesis to quantify changes in meridional and zonal temperature gradients throughout the Phanerozoic and to address the relative roles of individual forcings (greenhouse gases, solar, geography). While substantial effort has been made to quantify the evolution of global mean temperatures over the last 540 million years, changes in the large-scale temperature gradients and their causes are comparably less constrained. As a fundamental property of the climate system, changes in the spatial patterns of surface temperature play a critical role in controlling large-scale atmospheric and ocean circulation and influence hydrological, ecological, and land surface processes. The resulting best estimate product of meridional and zonal temperature gradients over the last 540 million years will represent a step change in our understanding of the drivers and consequences of past temperature gradient changes and will provide the community with a valuable resource for future climatological, geological, and ecological research.
No thick carbon dioxide atmosphere on the rocky exoplanet TRAPPIST-1 c
Authors: Zieba Sebastian , Kreidberg Laura , Ducrot Elsa , Gillon Michaël , Morley Caroline , Schaefer Laura , Tamburo Patrick , Koll Daniel D. B. , Lyu Xintong , Acuña Lorena , Agol Eric , Iyer Aishwarya R. , Hu Renyu , Lincowski Andrew P. , Meadows Victoria S. , Selsis Franck , Bolmont Emeline , Mandell Avi M. , Suissa Gabrielle
Published: March 2024

Seven rocky planets orbit the nearby dwarf star TRAPPIST-1, providing a unique opportunity to search for atmospheres on small planets outside the Solar System. Thanks to the recent launch of the James Webb Space Telescope (JWST), possible atmospheric constituents such as carbon dioxide (CO2) are now detectable. Recent JWST observations of the innermost planet TRAPPIST-1 b showed that it is most probably a bare rock without any CO2 in its atmosphere. Here we report the detection of thermal emission from the dayside of TRAPPIST-1 c with the Mid-Infrared Instrument (MIRI) on JWST at 15 µm. We measure a planet-to-star flux ratio of 421 +/- 94 parts per million (ppm), which corresponds to an inferred dayside brightness temperature of 380 +/- 31 K. This high dayside temperature disfavours a thick, CO2-rich atmosphere on the planet. The data rule out cloud-free O2/CO2 mixtures with surface pressures ranging from 10 bar (with 10 ppm CO2) to 0.1 bar (pure CO2). A Venus-analogue atmosphere with sulfuric acid clouds is also disfavoured at 2.6 sigma confidence. Thinner atmospheres or bare-rock surfaces are consistent with our measured planet-to-star flux ratio.
Improving Consistency in Methane Emission Quantification from the Natural Gas Distribution System across Measurement Devices
Authors: Tettenborn Judith , Zavala-Araiza Daniel , Stroeken Daan , Maazallahi Hossein , Hensen Arjan , Velzeboer Ilona , van den Bulk Pim , Vogel Felix , Gillespie Lawson , Ars Sebastien , France James , Röckmann Thomas
Published: March 2024

Efficient and cost-effective mitigation of methane emissions from local gas distribution systems requires full characterization of leaks across an urban region. Mobile real-time measurements of ambient CH4 provide a fast and effective approach to identify and quantify methane leaks. The objective of such methodologies is to relate emission rates to parameters obtained during mobile measurements. These parameters encompass the maximum methane enhancement detected while crossing a methane plume and the integrated area of the associated peak. The maximum enhancement is currently used for emission quantification in mobile measurements, but was suggested to exhibit inconsistency among various measurement devices. Based on controlled release experiments conducted in four cities (London, Toronto, Rotterdam, and Utrecht), emission estimation methodologies were evaluated. Integrated plume area was found to be a more robust metric across different methane gas analyzer devices than the maximum methane enhancement. A statistical function based on integrated plume area is proposed for more consistent emission estimations when using different instruments. Nevertheless, large temporal variations in CH4 concentration enhancements were observed for the same release rate in line with previous experiments. Evaluation of repeated measurements to address this uncertainty and enable differentiation among various leak sizes was included. This study recommends a minimum of three repeated measurements and an optimal range of 5-7 plume transects for effective emission quantification to prioritize repair actions.
Changes in the concurrence of atmospheric rivers and explosive cyclones in the North Atlantic
Authors: Lopez-Marti Ferran , Ginesta Mireia , Faranda Davide , Rutgersson Anna , Yiou Pascal , Wu Lichuan , Messori Gabriele
Published: March 2024

The explosive development of extratropical cyclones and the presence of atmospheric rivers play a crucial role in driving some types of extreme weather in the mid-latitudes, like compound flood-windstorm events. Although these phenomena are individually well-established and their relationship has been studied previously, there is still a gap in our understanding of how a warmer climate may affect their concurrence. Here, we focus on evaluating the current climatology and assessing changes in the future climate of the concurrence between atmospheric rivers and explosive cyclones in the North Atlantic.We use both the ERA5 and ERA-Interim reanalysis between 1980 to 2009 from October to March to evaluate the concurrence of atmospheric rivers and explosive cyclones in the current climate. To accomplish this, we first independently detect and track atmospheric rivers and extratropical cyclones. Next, we classify each cyclone as either explosive or non-explosive and define concurrence with an atmospheric river if the latter is detected within 1500 km of the minimum sea level pressure of the cyclone. We further analyse several CMIP6 climate models for the historical scenario (1980-2009) and for the future scenarios SSP1-2.6, SSP2-4.5 and SSP5-8.5 at the end of the century (2070-2099).Our findings reveal that atmospheric rivers are more often detected in the vicinity of explosive cyclones than non-explosive cyclones in all datasets. Moreover, we identified a significant increase in the concurrences and the atmospheric river intensity in all the future scenarios analysed. As such, our work provides a novel statistical relation between explosive cyclones and atmospheric rivers in climate projections, a characterization of both in future climates and a new climatology of the concurrences for a higher-resolution reanalysis.
Monitoring and forecasting subsurface geo-interfaces behavior of active slow-moving landslides using fiber optic nerve sensing system
Authors: Ye Xiao , Zhu Hong-Hu , Shi Bin , Catani Filippo
Published: March 2024

Monitoring evolution process of subsurface geo-interfaces in active slow-moving landslides can help understand landslide thermo-hydro-mechanical dynamics and predict potential landslide hazards. However, characterizing the behavior of these geo-interfaces and revealing their interactions remain challenging due to the general lack of high-resolution subsurface observations. To this end, we propose a novel fiber optic nerve sensing (FONS) system based on ultra-weak fiber Bragg grating (UWFBG) to sense the temperature, moisture and strain of geomaterials along a borehole in nearly real-time. The system is able to accurately locate and identify multiple potential slip surfaces and other critical geo-interface behaviors that may be relevant to landslide instability. The measurements confirm the foremost contribution of short-duration high-intensity extreme rainfall to accelerating landslide movement. We also attempted to employ machine learning algorithms based on classification principles to predict what hydrometeorological regimes would drive an accelerated deformation event. These subsurface data will allow us to investigate the multi-physical characteristics of geo-interfaces from daily to annual and even multi-annual scales and link cyclic thermo-hydro-mechanical external conditions to progressive failure. This work highlights the increasing impact of extreme weather events on landslide geohazards and the importance of multidisciplinary approaches for accurate prediction and early warning. Integrating FONS with remote sensing and ground-based technologies can create a comprehensive space-sky-ground-subsurface monitoring framework for landslides.
Echoes of change: deciphering environmental history through biomarkers investigation in sediment core from a Central Himalayan Lake
Authors: Yadav Ankit , Anoop Ambili , Mishra Praveen Kumar , Chirakkal Aljasil , Dietze Elisabeth
Published: March 2024

The dynamics and scale of anthropogenically induced environmental changes in the Indian Himalayas remain largely unexplored, presenting a complex and enigmatic challenge. To tackle this, we investigated the pollution, eutrophication and fire history of the last century by analyzing the concentration, compositional variation, and temporal trends in polycyclic aromatic hydrocarbons (PAHs), monosaccharide anhydrides, fecal biomarkers and other aliphatic hydrocarbons (n-alkanes, acyclic isoprenoids and botryococcenes) from a lake sediment core in the Central Himalayas at 2084 m asl. The study revealed that the concentration of total PAHs increased steadily with a compositional change after 1970, paralleling an increase in socio-economic activities in the region. The PAHs diagnostic ratios revealed that pyrogenic sources accounted for the majority of the sedimentary PAHs and the high correlation between PAHs and fecal stanols (r = 0.84, p 
Modelling CO2 and CH4 fluxes from drained and natural peatlands with the PEATLAND-VU model
Authors: van den Berg Merit , van Huissteden Jacobus , Lippmann Tanya T.R. , Boonman Jim , Buzacott Alexander J.V. , van der Velde Ype
Published: March 2024

Draining peatlands results in oxic soil conditions that causes microbial oxidation of peat. Drained peatlands are a large source for CO2 emissions, contributing 2-5% to the total anthropogenic greenhouse gas emissions. Understanding processes that contribute to peat oxidation are useful to simulate, predict and project CO2 emission in different environmental conditions. In wet conditions, soil is anoxic, which leads to an increase in methane (CH4) emission. Wetlands, including peatlands, are the largest natural source of CH4. Weather conditions, water table height, substrate availability, and vegetation type play a crucial role in the amount of CH4 that is emitted. The dynamic of CH4 production and oxidation, driven by the above mentioned factors, is complex. Nevertheless, for both CO2 and CH4, it is essential to be able to simulate these fluxes with a mechanistical model for monitoring and predicting greenhouse gas emission from peatlands.PEATLAND-VU is a 1D process based model, consisting of four submodels for 1) soil physics (water table, soil temperature and soil moisture), 2) biomass production, 3) CH4 production, oxidation and transport (diffusion, ebullition and plant transport), and 4) CO2 production. Here, CO2 production is represented as the sum of decomposition from different soil organic matter (SOM) pools, like litter, root exudates, microbial biomass, and peat.We calibrated the PEATLAND-VU model for two intensively used drained peat meadows and a wet Sphagnum-reed peatland in the Netherlands. These sites have 2-4 years of CO2 flux and CH4 flux (Sphagnum-reed peatland only) data. In our presentation we will show that the model performed well for simulating CO2 and CH4 fluxes. We will focus on the contribution of peat oxidation to the total CO2 emission, and show results of different water table management and future climate scenarios. Furthermore, for the Sphagnum-reed peatland the modelled CH4 production, CH4 oxidation, and the transport pathways resulting in the net CH4 flux will be discussed.
Ambiguity: Why does it hold a key role in the adaptation to climate change?
Authors: Brugnach Marcela
Published: March 2024

Ambiguity is a unique form of uncertainty that goes beyond merely indicating knowledge deficits or gaps; rather, it represents a state of confusion among decision actors. This confusion arises within a group due to the coexistence of diverse, and at times, conflicting meanings and interpretations concerning a situation. In the presence of ambiguity, it may not be clear what the main issues of concern are, who hold responsibility over them, what needs to be done. As an inherent characteristic of a collective, ambiguity is tightly linked with diversity and plurality, and the processes and procedures that underlie group dynamics. Here, I argue that ambiguity plays a pivotal role in adapting to climate change.To investigate the functioning of ambiguity, I draw upon (uncertainty) relational theory and analyse different study cases of water management. The results suggest that ambiguity can yield significant benefits in adaptation. It enhances flexibility in managing unknown conditions, enables the anticipation of conflicts and avoids maladaptation, and creates opportunities for establishing new supportive relationships and alternative solutions. These insights contribute to a nuanced understanding of the role of ambiguity in climate change adaptation, offering valuable guidance for policymakers, water managers, and stakeholders engaged in crafting resilient and sustainable water management strategies.
Impacts of long term P availability on Soil Organic Carbon stocks and cycling – insights from the EJP ICONICA project
Authors: Bhople Parag , Wall David , Richards Karl , Brennan Fiona , Lanigan Gary , Bondi Giulia
Published: March 2024

The management of agro-ecosystems enhancing soil and subsoil organic carbon (SOC) sequestration could be a potential strategy to mitigate climate change. However, soil quality and organic matter (SOM) transformation is highly regulated by the cycle and interactions with other nutrients such as carbon (C), nitrogen (N) and phosphorus (P). In agricultural management, the addition of P fertilizers and its effect on C and N cycling (CNP stoichiometry) is still largely unknown. Therefore, the ICONICA project intends to provide context-based information on soil nutrients (C & N) and their stocks and cycling in P fertilizer scenarios. To determine the influence that P fertilization has on SOC stabilizations and greenhouse gas (GHG) emissions in agricultural systems, ICONICA employed a unique set of long-term P fertilizer experiments (LTEs) across Europe, including a range of P treatments to establish relationship between long-term P availability and interaction with C and N. In this project soils up to 50 cm depth were collected from six LTEs distributed across Europe. The LTEs feature different soil type/textural classes and land uses. The objective was to quantify C stocks and provide initial reference value of soil C storage for soil depths and link that to the soil stoichiometric ratios (C:N:P) in different management systems. Overall, in grassland sites the average SOC stocks ranged from 54.76±6.65 (tC/ha) in The Netherlands, followed by 43.07±5.71 (tC/ha) in Ireland. The average SOC stocks in arable sites in Sweden were 21.22±1.19 (tC/ha) and the least SOC stocks (18.60±2.35 (tC/ha) occurred in arable site in Denmark. Grassland sites showed a higher SOC stock within the topsoil (0-10 cm) while arable sites contributes most of the C in the subsoil especially at 10-30 cm. The mean soil C/N ratio was higher in the topsoil (0-10 cm) in the arable with respect to the grasslands and ranged from 13.74 to 10.28 with similar trend at soil depth gradients. The variations in C flow and in stocks through the sampled profile of different land uses such as grassland to arable is highly complex and driven by multiple factors indicating the need for further assessment. Nevertheless, the observations indicated the indispensable nature of long-term field experiments to quantify the optimum C:N:P stoichiometry that may enable efficient SOC sequestration as opposed to production in the managed agricultural systems.