bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the efficiency of ensemble-based volcano deformation analyses using Machine Learning
Authors: Head Matthew , Gregg Patricia M.
Published: March 2024

Geodetic observations are key for assessing the unrest status of volcanoes worldwide, providing critical information about magmatic systems and the potential for magma migration and eruption. Analysing these signals relies on a robust data-model framework. One such approach is the Ensemble Kalman Filter (EnKF), a data assimilation method that has been adapted for analyses of volcanic deformation. The EnKF sequentially assimilates and inverts geodetic observations, using a series of model states to ‘nudge’ the model parameters with each iteration, reducing the misfit between the model and observation. We construct thermomechanical Finite Element (FE) models of volcanic regions, providing the necessary flexibility to incorporate complex 3D geometries and material heterogeneity. However, these simulations are computationally expensive when incorporated into the EnKF workflow, where an ensemble of >200 model states can take several hours to evaluate. This is particularly problematic for the analysis of observational data with high temporal resolution, such as daily GPS measurements.Here, we aim to reduce the computational cost of the EnKF-FE workflow by using regression machine learning algorithms (MLAs), focusing on reducing the number of model states that need to be evaluated by the FE models. We start by using the ‘Mogi’ deformation model, a simple analytical expression that calculates the three-component displacement field (Ux, Uy, and Uz) due to a point source. We employ a tuneable nearest-neighbour approach to identify model states that occupy a ‘similar’ parameter space, using MLAs to predict the resultant displacements. The Mogi model has significantly reduced complexity compared to that of a FE model, providing a simple platform to test different machine learning approaches. Preliminary results suggests that the k-Nearest Neighbours and Linear Regression algorithms can significantly improve the computational efficiency of the EnKF-FE workflow, with negligible impact on the inferred best-fit model parameters, when a magmatic system is in a steady-state (i.e., static overpressure). Future modelling efforts will consider FE models with a 3D deformation source within a flat-topped domain, and time-varying overpressure scenarios.
Disentangling the dynamics of the subpolar gyre and its interaction with the AMOC in the CMIP6 ensemble
Authors: Falkena Swinda , von der Heydt Anna
Published: March 2024

The subpolar gyre (SPG) is one of the climate tipping elements which could have a large impact on the climate in the northern hemisphere. Improving our understanding of its dynamics is key to assessing the likelihood of it passing a tipping point. Some CMIP6 models exhibit abrupt transitions in the sea surface temperature in the SPG region, but the majority does not. The differences in the model response can be related to the stratification bias, with many models having a too strong stratification preventing them from exhibiting bistable gyre dynamics.To better understand the SPG we study the (lagged) partial correlations between the relevant aspects of its dynamics in the CMIP6 ensemble. In contrast to standard correlations, partial correlations correct for the effect of autocorrelation and the effect of (the past of) other relevant variables. Therefore, it gives a better indication of there being a causal relation. Based on the partial correlation between the sea surface temperature and mixed layer depth we split the ensemble into two groups (strong or negligible relation) and for each select one model to study its dynamics in detail. In addition, we discuss the interaction of the SPG with the Atlantic Meridional Overturning Circulation (AMOC) using the same methods. These results can help in better informing more conceptual climate models of the SPG, AMOC and their interactions, which can be used to study potential tipping dynamics.
A deep learning approach for spatio-temporal prediction of stable water isotopes in soil moisture
Authors: Jung Hyekyeng , Soulsby Chris , Tetzlaff Dörthe
Published: March 2024

Water flows and related mixing dynamics in the unsaturated zone are difficult to measure directly, so stable water isotope tracers have been used successfully to quantify flux and storage dynamics and to constrain process-based hydrological models as proxy data. In this study, a data-driven model based on deep learning was adapted to interpolate and extrapolate spatio-temporal isotope signals of δ18O and δ2H in soil water in three dimensions. Further, this was also used to help quantify evapotranspiration and groundwater recharge processes in the unsaturated zone. To consider both spatial and temporal dependencies of water isotope signals in the model design, the output space was decomposed into temporal basis functions and spatial coefficients using singular value decomposition. Then, temporal functions and spatial coefficients were predicted separately by specialized deep learning models in interdependencies among target data, such as the LSTM model and convolutional neural network. Finally, the predictions by the models were integrated and analyzed post-hoc using XAI tools.Such an integrated framework has the potential to improve understanding of model behavior based on features (e.g., climate, hydrological component) connected to either temporal or spatial information. Furthermore, the model can serve as a surrogate model for process-based hydrological models, improving the use of process-based models as learning tools.
IMERG-E and IMERG-L: A Comprehensive Evaluation of the Medicane Daniel in Thessaly, Greece
Authors: Leivadiotis Evangelos , Kohnová Silvia , Psilovikos Aris
Published: March 2024

On 4 September 2023, the area of Thessaly (Greece) experienced a catastrophic flood as a result of the Daniel hurricane sequence. This severe phenomenon is characterized by extreme rainfall records ranging from 305 mm to 1096 mm between 4 and 7 September, causing severe damage to infrastructure, agriculture and buildings. Seventeen casaulties were recorded. The aim of the study is to complete the integrated multi-satellite harvesting of the Global Precipitation Measurement Mission (IMERG) using 10 precipitation stations distributed in the Thessaly region. Specifically, two precipitation products (IMERG-E and IMERG-L) were used to evaluate the early and late extreme precipitation events of IMERG version 7. In order to obtain the rainfall data needed for the research, a time period of 4 September 2023 (0000UTC) to 7 September 2023 (2330UTC) was chosen. This window corresponds to the approximate time at which Daniel's storm convective zone was on the area of interest. The National Meteorological Agency collected six of the ten precipitation stations and four of the Public Electricity Agency. The evaluation process was divided into two parts: the first part aimed at estimating the total rainfall of IMERG-E and IMERG-L, and the second part aimed at estimating the total daily rainfall of both products. Two statistical assessment indicators were used: the Pearson correlation coefficient and the root mean square error (RMSE) to quantitatively assess the performance of satellite precipitation products using rain-gauge data. Firstly, the correlation coefficient between IMERG-E, IMERG-L and total precipitation at IMERG-E, IMERG-L and IMERG-L is -0.03 and 0.27, respectively. Early products did not correlate with ground data, but later versions showed weak positive linear relationships. The RMSE values are 0.8 and 0.52, respectively. The daily analyses of IMERG-E showed moderate negative correlations on September 4 (-0.29), September 5 (-0.15), and September 7 (-0.25), and moderate positive correlations on September 6 (0.37). In terms of daily performance, the correlation coefficients suggest weak positive correlations (0.22 in 4 September, 0.13 in 5 September, 0.23 in 7 September), with the exception of -0.3 in 6 September. RMSE values remain low (0.31 on 4 September, 0.34 on 5 September, 0.20 on 7 September), except for 6, September, where values (0.95) indicate high levels of error. Overall, the late version is more efficient than the early version, but there are rooms for improvements when the IMERG final version will be available.
Using a simple model to measure the differences between climate model land surface simulations and FLUXNET observations
Authors: Lambert F. Hugo , Zarakas Claire , Natchiar S. R. Monisha , Swann Abigail L. S. , Koven Charles D.
Published: March 2024

Complex numerical models of climate consist of simulation of fluid dynamics and thermodynamics on a discrete grid, and parameterizations, which are algorithms that approximate processes smaller than gridscale. Because parameterizations of a given process may be written as different functions of different, potentially non-observable variables, it can be difficult to quantify the process differences between individual climate models and between climate models and the real world.Here, we attempt to write down a simple linear model that represents the response of the Earth's tropical land surface to atmospheric forcing on monthly timescales in terms of the same observable variables using a technique called continuous structural parameterization. Simulated data are taken from complex General Circulation Models (GCMs) run under the AMIP protocol and a CESM2 perturbed physics ensemble (PPE) of our own devising;  observed measurements are taken from FLUXNET flux tower sites. We find that the simple model captures land surface behaviour well except in mountainous regions.Establishing a generalised parameter space, we see that most GCMs are in reasonable agreement with FLUXNET at FLUXNET sites, although there is evidence that GCMs consistently slightly overestimate the response of surface turbulent fluxes to downward radiation. Further, it is found that the differences between structurally different AMIP models are considerably greater than the differences between CESM2 PPE members -- even though the PPE parameters are varied across their realistic domain. If the simple model is trained only at GCM spatial gridpoints that contain a FLUXNET site, there is little degradation in simple model performance compared with global training, suggesting that even the few available tropical FLUXNET sites are useful for constraining land surface model response throughout the tropics. This is of course contingent on whether or not point measurements taken by FLUXNET are representative of the wider area around FLUXNET sites.
Evaluation of habitat diversity and water quality preferences of macroinvertebrates through fuzzy coding
Authors: Park Jinhee , Yoon Jin-Ho , Kim Sang Don
Published: March 2024

Hydrology evaluates habitat diversity and quality by identifying where living organisms prefer the environment through habitat information. This information significantly influences biodiversity conservation and the survival of various organisms. Moreover, understanding the types and characteristics of aquatic organisms contributes to determining water quality. This study used a hydrological approach to understand the interaction between the environment and organisms with data on the geographical distribution of freshwater organisms and the various water quality conditions in their respective habitats. Specifically, fuzzy coding was applied to integrate the geographical distribution of over 200 macroinvertebrates in Korea with various water quality conditions (i.e., pH, total phosphates, total nitrogen, etc.) in their preferred habitats. Fuzzy coding quantified the affinity of species for various water quality parameters (e.g., pH) composed of ambiguous or overlapping modalities (e.g., acidic, neutral, and base), constructing fuzzy-coded species x environmental gradient matrices for each species. The resulting database will be critical in evaluating habitat diversity and quality for aquatic organisms from a hydrological perspective. It can be used as an indicator for habitat and biodiversity conservation. It will also provide important information for assessing organisms' adaptability to environmental changes based on their preferences for water quality conditions. Moreover, the database can contribute to establishing policies on water pollution and conservation by understanding the water characteristics preferred by a given organism. Further study is needed to understand the ecological impact of habitat changes due to environmental variations and appropriate modeling to predict water quality changes.
Integration of relational geodatabase in a web-GIS platform for Mapping the effects of Mediterranean Cyclone.
Authors: Kushabaha Alok , Scardino Giovanni , Sabato Gaetano , Scicchitano Giovanni , Borzi Alfio Marco
Published: March 2024

Several cyclogenesis processes affect the Mediterranean Sea, causing significant impacts along its coastline. This study focuses on mapping the effects of cyclones in the Mediterranean Sea, particularly Mediterranean hurricanes, which cause severe damage to coastal areas. Advanced remote sensing and Geographic Information System (GIS) techniques are used to analyse climatic data and observe geomorphological evidence, such as flooding, coastal erosion, landslides, alluvial flooding and debris flow. By integrating climate features and geomorphological evidence, this research establishes a connection with the occurrence of Mediterranean cyclones. The study specifically examines the south-eastern coasts of Sicily, where Mediterranean Hurricanes have caused extensive damages, including flooding, erosion, and storm surges. Pre and post-storm morpho-topographical surveys were conducted to assess coastal flooding and erosion through aerial photogrammetry and Terrestrial Laser Scanner surveys. The collected data were stored in a geodatabase, allowing for the display of climate features and geomorphological evidence. Additionally, the development of an open-source Web-GIS platform integrated with the geodatabase can facilitate the dissemination of geographic information to stakeholders and researchers, promoting collaboration and informed decision-making. This study contributes to a better understanding of Mediterranean cyclones, enabling the development of effective coastal management strategies to mitigate the challenges posed by Mediterranean Hurricanes.
Revealing dominant controls in a continental-scale model of submarine groundwater discharge and seawater intrusion by utilizing intrinsic model variability
Authors: Kretschmer Daniel , Moosdorf Nils , Michael Holly , Wagener Thorsten , Reinecke Robert
Published: March 2024

Groundwater is vital to sustain coastal freshwater consumption and agricultural activities around the globe. In the US, groundwater withdrawal has more than doubled from 1950 to 2015. In 2015, almost half of the coastal counties in the US relied on groundwater as their primary water source. Large volumes of groundwater withdrawal at the coast have caused groundwater level declines: almost half (44%) of the well water level observations made within 1 km of the coast are below sea level. We know that such reduction of groundwater reduces the amount of fresh submarine groundwater discharge (SGD) - fresh groundwater flowing into the ocean - and may trigger seawater intrusion (SWI), harming coastal ecosystems and deteriorating groundwater quality for domestic and agricultural use. Previous continental-scale and global models of SGD and SWI have simulated steady state conditions. To understand which factors drive these two fluxes and how coastal aquifers are impacted by sea level rise and changes in groundwater recharge, we have developed a MODFLOW-like modeling framework that can simulate transient density-driven groundwater fluxes on large scales (G³M-D). For our investigation, we focus on a simulation of North America. The model simulates SWI as an interface between potable and non-potable (i.e., too saline) groundwater. Established sensitivity-analysis methods that would allow pinpointing dominant controls inside a model often require hundreds to thousands of model simulations. Here, we utilize the intrinsic variability of the model to analyze drivers of coastal groundwater exchange. We show which factors drive the exchange fluxes between groundwater and ocean for different model domains. We also discuss whether the large-scale representation fits our perceptual model of coastal processes.
Low cost, rapid method for ambient particulate matter speciation in specific environments
Authors: Varghese George K , Regi Anson , Mohan Prem , Ponnachan Jijo
Published: March 2024

Chemical speciation of ambient particulate matter (PM) is important for understanding the health effects of this most ubiquitous air pollutant. Many studies in India have reported significant contribution of road dust to ambient PM, in some cases as high as 70%. This study presents a quick and affordable method for knowing the approximate chemical composition of the atmospheric PM from the chemical analysis of sediment deposits from ground surface. Sediment from street surface was collected and segregated into different size fractions using sieves. Chemical characterization was done separately for each size fraction, and from the results the composition of dust particles of size less than 10µm was obtained. Ambient PM was monitored using MiniLAS, which is a real time PM monitoring instrument that measures PM in 24 different size channels. Using size as criteria, the fraction of road dust in ambient PM was determined. Now, combining the results of ambient PM monitoring and chemical characterization of street dust, the chemical composition of atmospheric PM was calculated. To confirm the results, PM collected in a high-volume air sampler deployed at the place was analyzed for chemical composition. The results matched with the calculated composition indicating the possibility of adopting this method for environments polluted with resuspended dust, which is very often the case in developing countries.
Predicting annual base flow index and its trends using a large sample of dataset across the globe
Authors: Huang Qi , Seibert Jan , Zhang Yongqiang
Published: March 2024

The Base-Flow Indices (BFI), indicating surface and groundwater interaction, play a significant role in the hydrological cycle. The values vary widely across the globe, and are expected to change in the context of a changing climate. Predicting global “natural” BFI is challenging due to limited observations reflecting natural impacts. This study aims to predict annual BFI and their trends for a compiled dataset of annual streamflow and meteorological data covering the period 1982-2020 for more than 2250 small unregulated catchments worldwide. BFI were derived using three digital filtering methods, resulting in a trend of -0.0009 ± 0.01 per decade over the last four decades. To predict annual BFI and their trends in ungauged catchments, a Random Forest Regression approach was employed, incorporating static attributes and meteorological time series data as model inputs. Five-fold cross-validation demonstrated the effectiveness of the Random Forest Regression in predicting both BFI and their trends. The Quantile Regression Forest method was utilized to quantify the uncertainty, achieving a relatively low range for both BFI and their trends. Soil conditions and maximum temperature emerged as the most crucial variables for predicting BFI, while temperature-related variables also proved essential for predicting the BFI trends. The goal is to extend the understanding of "natural" BFI and their trends in ungauged catchments, as the Random Forest Regression model was trained under unregulated conditions. This study offers the possibility to predict "natural" BFI and their trendsacross the globe. This could support water authorities in managing water resources, particularly concerning base flow.
Model-based evaluation of the impact and longevity of a novel sustainable subsoil melioration method (Soil³ method) on root growth 
Authors: Selzner Tobias , Berns Anne E. , Leitner Daniel , Schnepf Andrea
Published: March 2024

The subsoil, commonly defined as the soil beneath the tilled or formerly tilled soil horizon, contains large amounts of nutrients and water. Large fractions of these subsoil resources are not readily available to agricultural crops due to compacted layers of high bulk density. Although there are conventional methods for loosening compacted subsoils (e.g., mechanical subsoiling and deep ploughing), their effects are often quickly reversed or can even be harmful to the soil structure. Eventually, the brief enhancement in subsoil access for crops is often insufficient to justify the considerable expenses associated with the methods. To facilitate a more efficient use of subsoil resources, the Soil³ project for sustainable subsoil melioration derived a novel  approach, which is carried out in a single crossing of the field. First, the top soil of a 30 cm wide strip is excavated and deposited on the soil surface beside the strip, creating a furrow. The subsoil in this furrow (30-60 cm depth) is then loosened and intermixed with organic material (e.g., compost). After mixing, the excavated topsoil is lead back into the furrow, thus closing it again. The method therefore preserves the natural soil structure by not mixing the top and subsoil substrates, while the loosened subsoil structure is stabilized by incorporating organic material. Additionally, the operating costs are kept reasonable by only loosening the soil in a strip-wise manner.Here, we use and extend the 3D functional-structural plant model CPlantBox to investigate the impact of the Soil³ method on root growth. On the soil side, we employ pedo-transfer functions to model the evolution of soil bulk density (soil setting) and the resulting changes in soil hydraulic properties in time. The pedo-transfer functions are parameterized based on data of the Soil³ field trials and are solved for different soil depths, as well as for the soil layers on and beside the melioration strips. In our model, we account for the time-dependent changes in soil hydraulic properties of all soil layers by implementing the usage of variable Van-Genuchten parameter sets within a single simulation run. Based on the parameterized soil domain, we simulate root growth and root water uptake from the different soil layers. Experimental data is used to parameterize general root growth parameters (e.g., root length density, planting density, transpiration). The explicit 3D root system architecture, however, is a result of the model, and its growth is modeled as a function of bulk density, water content and penetration resistance. By performing virtual replications of the field trials over multiple consecutive years, we can evaluate the impact and longevity of the subsoil melioration on root growth and its underlying processes.
Temperature Forecasting with Markov Expert Aggregations
Authors: Wintenberger Olivier , Pfitzner Leo , Mestre Olivier
Published: March 2024

A multitude of Numerical Weather Prediction (NWP) models, along with their associated Model Output Statistics (MOS), are readily available. Expert Aggregation (EA) algorithms combine them in an online and adaptive manner. While EA competes optimally against the best-fixed combination of experts (Wintenberger 2017), it falls short in handling rapid changes. We introduce the class of Markov-EA algorithms, extending the seminal work of Mourtada and Maillard (2017) on Exponentiated Weights to other EA algorithms such as BOA and ML-Poly. Understanding how and when to adjust the weights is crucial for obtaining optimal second-order regret bounds. Assuming a (non-homogeneous) Markovian dynamic, we enhance the EA predictions of short and poorly predicted events, such as the cold event in the Chamonix valley, using weight sharing and strategies involving sleeping experts. This work is done in collaboration with Leo Pfitzner and Olivier Mestre (Météo France).
The sensitivity of the PETM carbon cycle perturbation to orbital configurations
Authors: Papadomanolaki Nina M. , De Vleeschouwer David
Published: March 2024

It is generally postulated that climatic change during the Paleocene – Eocene Thermal Maximum (PETM) was paced and/or caused by astronomical forcing, particularly eccentricity-modulated precession. Possible causal links include intermediate water warming and subsequent methane hydrate destabilization, increased climate sensitivity due to a warmer background state, and changes in hydrology and weathering. Current astrochronology places the PETM near a 405-kyr eccentricity maximum (Zeebe and Lourens, 2019), likely following a prolonged 2.25-Myr eccentricity minimum (Lourens et al., 2005). Similar orbital configuration sequences have been proposed for the Devonian Upper Kellwasser event (De Vleeschouwer et al., 2017) and the Cretaceous Oceanic Anoxic Event 2 (Batenburg et al., 2016). To understand how eccentricity could have made the Late Paleocene Earth System sensitive to a carbon-cycle perturbation with the amplitude of the PETM, we investigate both the equilibrium and transient climate response to changes in insolation. Specifically, our experimental set-up is to identify how rapid climate change events may unfold differently under high eccentricity (PETM) and low eccentricity (modern) regimes. We present results from equilibrium climate state simulations and transient climate responses to PETM emission scenarios, using the cGENIE Earth system model under a comprehensive set of eccentricity/precession configurations. Based on the outcomes of these simulations, we describe the differences in PETM expression in terms of climate and weathering regimes, depending on the astronomical configuration.
High pressure phase of Magnesiowustite: Implications to the mineralogy of super-Earths
Authors: Karangara Anjitha , Das Pratik Kumar
Published: March 2024

Recent years have seen the discovery of a huge number of exoplanets, including several planets with very high densities suggesting that they also have rocky interiors which may be 9 – 10 times more massive than Earth. Mineralogy of these so called ‘super-Earth’ planets have been an interesting topic, as it gives implications on the planetary processes (Plate tectonics, geodynamo, etc.) and their habitability. Many studies concluded that such planets may contain ultra-high-pressure analogues of Earth’s lower mantle minerals. (Mg,Fe)O, a binary solid solution of MgO-FeO system is the second most abundant mineral of Earth’s lower mantle. If these super-Earth’s interior can have high pressure analogue of perovskite which is another most abundant phase of lower mantle of Earth as shown by some recent studies then there is a possibility of finding high pressure phase of (Mg,Fe)O also in the lower mantle of those super-Earths. MgO is stable in a NaCl structure (B1) in lower mantle condition of earth. It transforms to CsCl2 (B2) at high pressure (p) and Temperature (T) conditions. However, FeO is stable in B1 structure which transforms to a rhombohedral phase first and then to NiAs-type structure (B8) with increasing p. Finally, above 240 GPa and 4000 K, FeO transforms directly from B1 to B2. Along with structural phase transitions, FeO also undergoes a spin transition from high spin (HS) to low spin (LS) state with increasing pressure. In this study, we performed first principles DFT calculations on the structural phase transitions of MgxFe1-xO (x % = 0, 25, 50, 75 & 100) from B1 to B2 coupled with spin transition. Their mechanical and thermal properties under pressures ranging from 0 – 500 GPa relevant to super-earth planets have also been estimated. Our investigations have confirmed the presence of B1 phase of (Mg,Fe)O in lower mantle of earth with a spin transition from HS -LS which is thought to be responsible for the seismic anomalies of lower mantle of Earth. Spin transition of magnesiowustite and its effect on mechanical and thermal properties have been the topic for several experimental studies for many years. Most of them tried to explain the shear anisotropy of lower mantle with the help of (Mg,Fe)O with various Fe concentrations. Present study attempts to explore the stable phases of MgxFe1-xO relevant to super-Earth conditions. Both mechanical and dynamical behaviour have been investigated in the entire pressure range. Results show a new tetragonal phase of Mg0.25Fe0.75O above 125 GPa, which is found to be both mechanically and dynamically stable. These findings will also attempt to predict the mineralogy and seismicity of those giant planets.
Mapping release and propagation areas of permafrost-related rock slope failures in the French Alps: A new methodological approach at regional scale
Authors: Cathala Maeva , Magnin Florence , Ravanel Ludovic , Dorren Luuk , Zuanon Nicolas , Berger Frederic , Bourrier Franck , Deline Philip
Published: March 2024

Permafrost-affected rockwalls are increasingly impacted by the effects of climate change and rising air temperature leading to rock slope failures, threatening human lives and infrastructure. Populations and policy makers need new methods to anticipate these potential hazards and their consequences.  The aim of this study was to propose a mapping approach of susceptible release areas of rock slope failures and resulting runout distances at a regional scale to identify hotspots for hazard assessment.To do so, we used an inventory of 1389 rock slope failures (volume > 102 m3)recorded in the Mont-Blanc massif from 2007 to 2019 and determined the topographical and permafrost conditions that are most prone to their triggering using a digital terrain model and a permafrost map. These conditions are used in a multi-criteria GIS approach to identify potential unstable slopes at the French Alps scale. Then, the potential release area map is used as input to map the runout of potential events, using a propagation model based on a normalised area dependant energy line principle. The resulting maps of release and propagation areas could be used to point out human assets and lakes which could be impacted by rock slope failure hazards. In this communication we will show how theses maps can be used to identify potential hotspots for a regional hazard assessment.This work is a first step to identify hot spots for a regional hazard assessment where more detailed analyses will be required to evaluate potential risks at a local scale.
Validation of EarthCARE Cloud and Precipitation Products through the WegenerNet 3D Open-Air Laboratory facilities
Authors: Fuchsberger Jürgen , Kvas Andreas , Kirchengast Gottfried , Foelsche Ulrich , Ghaemi Esmail , Galovic Robert , Scheidl Daniel , Bichler Christoph
Published: March 2024

The WegenerNet 3D Open-Air Laboratory for Climate Change Research, located in southeastern Austria in an area of about 22 km x 16 km around the city of Feldbach (46.93°N, 15.90°E), provides a unique setup for atmospheric monitoring and validation of satellite data products. Its 3D instrumentation consists of a polarimetric X-band Doppler weather radar, a microwave radiometer for vertical profiling of temperature, humidity, and cloud liquid water, an infrared cloud structure radiometer, and a water-vapor-mapping GNSS station network. These 3D sensors complement the high-density WegenerNet hydrometeorological ground station network, which is comprised of 156 stations measuring precipitation, temperature, humidity, and (at selected locations) wind as well as soil parameters.This highly synergistic measurement setup enables robust internal cross-evaluation, calibration and quality control for obtaining reliable observations and derived WegenerNet data products. The 3D instrumentation is operational since mid-2021 and will provide a consistent validation reference data record throughout the EarthCARE mission lifetime. With its ground-based observations of cloud base height, melting layer base and top heights, liquid water content, precipitation rates, and hydrometeor classification, the WegenerNet contributes specifically to the validation of EarthCARE L2a and L2b cloud and precipitation data products. This presentation summarizes the validation preparation activities carried out so far, with focus on the EarthCARE validation rehearsal, and gives an outlook on the planned post-launch validation work during the actual cal/val phase.
First approach to the rheological behaviour of syn-eruptive and post-eruptive lahars.
Authors: Tranquilino Carla , Caballero Lizeth , Flores Guzmán Mario , Sarocchi Damiano , Dioguardi Fabio
Published: March 2024

Lahars are two-phase gravity flows which behavior strongly depends on the interaction between the solid phase (large clasts) and the liquid phase (interstitial fluid or matrix). In particular, the rheological behavior of the interstitial fluid is the parameter with the greatest influence on the lahar movement, since the interstitial fluid controls the transportion and sedimentation of the solid phase. The characteristics that define the rheological behavior of the interstitial fluid are particle volumetric concentration, size distribution, and sediment composition. Because of these, here we present the rheological characterization of syn-eruptive and post-eruptive lahars occurred at Popocatepetl volcano, Mexico.The interstitial fluid characterization was carried out by a strain rate dependence test using a rotational viscometer with a coaxial cylinder geometry. We studied volcanic sediments with different densities and compositions (pumice and lava fragments) sampled from syn- and post-eruptive lahar deposits (at room temperature). In addition, we studied the range of the volumetric sediment concentration that defines the flowage based on the geotechnical characteristics of sediments.The results suggest a Bingham-type behaviour model with yield strength values between 10-2 and 100 Pa, for shear rate conditions between 50 and 100 s-1. In addition, an inverse relationship of apparent viscosity throw values between 10-2 and 10-1 Pa s at  the same shear rates, suggesting a thinning behaviour. The data suggest exponential relationships between volumetric sediment concentration and yield strength or apparent viscosity. The fitting coefficients describe volcanic sediments, unlike those found in the literature and often used in lahar simulations for hazard modelling, which are derived from the study of soil materials and mine tailings.The interstitial fluid of syn-eruptive lahars with monolithologic composition (pumice fragments) has yield strength and apparent viscosity values higher than those of syn-eruptive and post-eruptive lahars with heterolithologic composition (pumice and lava fragments). In addition, the dominant clay-sized interstitial fluid has apparent viscosity values between two and three orders of magnitude higher than the dominant silt-sized interstitial fluid.Finally, the rheological behavior of the studied lahar samples will contribute to solving  the constitutive equations that describe their movement under a viscoelastic flow behavior for the studied shear rates. Furthermore, this information could be implemented in numerical simulations with similar volcanic sediment characteristics and deformation conditions to those studied, with the aim of estimating the inundation area that would be affected by the occurrence of a similar event.  
Joint use of machine learning and geostationary satellite data for volcanic ash cloud detection
Authors: Torrisi Federica , Corradino Claudia , Cariello Simona , Lopez Taryn , Del Negro Ciro
Published: March 2024

During an explosive eruption, a major hazard to population can be represented by the ejection in the atmosphere of gases and ash, with the consequent creation of volcanic clouds, which can compromise aviation safety. The combined use of a variety of satellite data in different spectral ranges with diverse spatial and temporal resolutions allows us to continuously monitor volcanic ash clouds in an efficient and timely manner. Specifically, the latest generation of high temporal resolution satellite sensors, such as EUMETSAT MSG Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and GOES18 Advanced Baseline Imager (ABI), provide almost continuous radiometric estimates to track the entire evolution of volcanic clouds produced by worldwide volcanoes. Therefore, leveraging the strengths of these satellite sensors, which provide frequent observations at a wide variety of wavelengths, can provide critical information to help understand volcanic processes and extract eruptive products. Nevertheless, the satellite data volume is too large for ad hoc processing and analysis especially when considering daily global-scale observations. Deep learning (DL), a fastest-growing technique of artificial intelligence in remote sensing data analysis applications, has an excellent ability to learn massive, high-dimensional image features and has been widely studied and applied in classification, recognition, and detection tasks involving satellite imagery.Here, we developed a new DL model, based on Deep Convolutional Neural Networks (CNNs), which exploits a variety of spatiotemporal information mainly coming from geostationary satellite sensors. It is trained on a combination of Thermal Infrared (TIR) bands acquired by MSG-SEVIRI and GOES18-ABI. The proposed model aims to extract complex spectral and spatial patterns autonomously to recognize a volcanic ash cloud. Preliminary capabilities and limitations of this model will be presented here. Thanks to the wide area covered by these satellite sensors, it is possible to apply this model to different volcanoes. Specifically, this model has been applied to the paroxysmal events that occurred at Mt. Etna (Italy) between 2020 and 2020 and at Shishaldin (Alaska, USA) in 2023.
Stratigraphic correlation across the western to central Arctic Ocean for Quaternary Paleoenvironmental reconstruction
Authors: Park Kwangkyu
Published: March 2024

The Arctic Ocean is one of Earth's most dynamically evolving regions, especially for orbital timescale during the Quaternary marked by the waxing and waning of continental ice sheets in the circum-Arctic. The consequential environmental shifts have been imprinted in marine sedimentary deposits in the Arctic Ocean, rendering them invaluable for paleoclimatic and paleoceanographic subjects. Despite their potential significance, the accurate chronology of these sediment records remains debatable due to numerous uncertainties from different dating methods, resulting in difficulties in paleoenvironmental reconstruction. Even widely used absolute age measurement techniques, for example, such as radiocarbon dating using calcareous microfossils, have exhibited limitations in certain cases. To address these challenges and enhance the precision of age determination for Arctic Ocean marine sediments, this study aims to assess and compare various dating methods comprehensively. By critically examining their strengths and weaknesses, it can be sought to establish a more robust framework for constraining the ages of marine sedimentary sequences in the Arctic Ocean. Additionally, this research endeavors to explore the implications of improved chronological accuracy for reconstructing paleoenvironmental conditions in the Arctic Ocean. By refining the timeline of past events, it can be anticipated that a clearer picture of the interplay between ice sheet dynamics, oceanic circulation, and climatic variations will emerge.
Ensemble analogue methodology for the forecast of turbulent properties in the solar wind 
Authors: Simon Pauline , Chen Christopher
Published: March 2024

The solar wind is a plasma which is known to be highly turbulent. The subsequent non-linear cascades of, for instance, energy influence the behaviour at a wide range of scales of the observable quantities, such as the magnetic field and velocity. The small-scale behaviour can be seen as an a priori predictable “noise” that could impact space weather forecasts. Such an impact is usually neglected because the resolution of solar wind forecast models is not sufficient, due to computational limitations. As a first step in the turbulent-oriented improvement of space weather forecasts, we have tackled the question of how predictable different aspects of the small-scale turbulence in the solar wind are. We have used the ensemble analogue methodology, which assumes that future events are predictable based on what has happened in the past, and test this on the solar wind turbulence properties. We will discuss our results in terms of their implications for solar wind and space weather forecasting.
Understanding the carbon sequestration in the mountain dry forest (MDF) situated in the southern part of Ecuador inferred from eddy-covariance measurements
Authors: Murkute Charuta , Sayeed Mostafa , Pucha Cofrep Franz , Raffelsbauer Volker , Ahmed Rezwan , Scholz Sebastian , Limberger Oliver , Carillo-Rojas Galo , Bendix Jörg , Trachte Katja
Published: March 2024

Forests are vital carbon sinks, absorbing and storing large amounts of carbon dioxide (CO2) through photosynthesis. Thus, forest ecosystems strongly contribute to climate change mitigation inducing a carbon sink function. Whether a forest is acting as a source or sink is highly dependent on the microclimatological conditions of the region in terms of the heat and water budget. Our study area is the mountain dry forest (MDF) on the western flank of the Andes Mountains in southern Ecuador, i.e. the Tumbesian dry forest of the Laipuna Reserve. The climate of the region is characterized by a strong seasonality influenced by the interhemispheric shift of the ITCZ, which result in a distinct dry (June - December) and wet (January - May) season. However, this seasonality can render these ecosystems susceptible to fluctuations in precipitation and temperature patterns, including prolonged drought periods that adversely impact tree regrowth. Consequently, the MDF becomes vulnerable to the effects of climate change. In contrast, the trees in the MDF also exhibit adaptations that enable them to withstand drought conditions, which may feature a higher resilience against climate change.To understand the driving processes of carbon and water exchanges over the MDF and response to climate change, an eddy covariance flux tower has been installed over the canopy. The tower is equipped with an open-path Irgason system (Campbell Sci. Inc.) to obtain net-ecosystem exchange (NEE) and evapotranspiration (ET) as well as additional meteorological sensors to measure precipitation, net-radiation and soil conditions. Additionally, soil CO2 efflux measurements are used to estimate the below-ground carbon exchange and its contribution to the total above-canopy signal.Our main focus is on the quantification of the carbon storage capacity and its variations according to the clearly pronounced seasonality. Further, since water scarcity and heat stress impact the carbon sequestration, we also aim to analyze climate stress situations and its effect on the carbon exchange. For this, NEE is partitioned into GPP (Gross Primary Productivity) and Reco (Ecosystem Respiration) to get insight into carbon uptake by photosynthesis and carbon release by respiration. The preliminary results of the study show that during the wet season the ecosystem generally acts as a carbon sink (GPP = 188 gCm-2month-1, Reco = 155 gCm-2month-1), while during the dry season it oscillates around neutrality. However, considering the transition periods, a stronger dependency to the climate conditions can be observed, which creates alternating patterns of carbon sink and sources. 
Coupling hydrostatic and non-hydrostatic ocean circulation models. Vertical modes perspective.
Authors: Lozano Pierre
Published: March 2024

Large-scale ocean modeling relies on the so-called primitive equations, which are a simplified form of the Navier-Stokes equations based on common assumptions. These assumptions include the Boussinesq approximation, the hydrostatic assumption and the incompressibility hypothesis. The hydrostatic assumption is yet no longer valid in the framework of high-resolution regional ocean modeling and is thus to be removed, leading to a significant increase in the computational load of the model. This gives rise to consideration of model coupling, where the hydrostatic assumption is selectively lifted within specific regions of the computational domain. This is the subject of this work.One of the primary challenges involves accurately representing the various types of waves that propagate in the ocean. Waves are studied by analyzing the dispersion relations after linearizing the equations. A key distinction between hydrostatic and non-hydrostatic modeling lies in the dispersive nature of the wave propragation in the latter. We initially explore an idealized scenario by coupling a transport equation with a Korteweg-de Vries equation. To manage dispersive effects, we employ Perfectly Matched Layers (PML), typically used for replicating absorbing boundary conditions, they can also be regarded as a buffer zone for filtering dispersive effects.Expanding this approach into a three-dimensional framework involves projecting the vertical ocean structure onto vertical modes associated with the ocean's background vertical stratification. We show that this projection allows us to reduce the problem to the previously studied case.
The Castanhão EPISODE - the case study of Reservoir Induced Seismicity (RIS) in NE Brazil.
Authors: Ciechowska Helena , Rudziński Łukasz , Orlecka-Sikora Beata , Vuan Alessandro , Kostoglou Anastasios , Nascimento Aderson Farias do
Published: March 2024

The man-made alteration to the environment can become a source of seismic activity. The Castanhão region (Ceará, NE Brazil) can pose as an example of such. The Castanhão Reservoir was created as a result of dam construction over the Jaguaribe River, which triggered the occurrence of earthquake swarms on the site. In the following study, we aim to analyze the data and understand the seismic mechanism behind the seismic activity in the Castanhão region. Such study required an interdisciplinary approach employing data from various disciplines such as seismology, geology, geomechanics, and hydrology. The starting data set contains continuous waveforms recorded on 6 seismological stations from January to December 2010. The two detection algorithms were applied for earthquake detection. Initial detection was performed with the use of the STA/LTA algorithm, which allowed for the preparation of 53 templates with a good S/N ratio. Further, in the frequency range from 5 to 100 Hz, the input templates were used to match self-similar events to augment the initial catalog.Due to the station coverage and low magnitude of the events, the detailed analysis of the quakes is performed on 187 events out of over 300 that were detected during PyMPA template matching. The localization was performed using Hypo71 software and analysis of mechanisms is done with the KiwiTool. The Castanhão EPISODE is planned to be made available on the EPISODES Platform of EPOS Thematic Core Services Anthropogenic Hazards.