bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydrocarbon-bearing fluid migration produces brecciation at high pressure condition in subduction
Authors: Giuntoli Francesco , Menegon Luca , Siron Guillaume , Cognigni Flavio , Leroux Hugues , Compagnoni Roberto , Rossi Marco , Vitale Brovarone Alberto
Published: February 2023

It has been recently proposed that high-pressure genesis of abiotic hydrocarbon can lead to strain localization in subducted carbonate rocks1. However, the mechanical effects of the migration of these hydrocarbon-bearing fluids on the infiltrated rocks still need to be constrained.In this study, we investigate omphacitite (i.e. omphacite-rich rock) adjacent to a high-pressure methane-rich fluid source from the Western Italian Alps (Italy) using a multiscale and analytical approach including petrographic, microstructural, X-ray compositional mapping and electron backscatter diffraction analyses (EBSD). In the field, omphacitite bands are 1-5 metres thick and tens of metres long and are adjacent to carbonate rocks affected by high-pressure reduction and methane-rich fluid production.Hand specimens and thin sections display a brecciated structure, with omphacitite fragments ranging in size from a few microns to several centimetres, surrounded by a matrix of jadeite, omphacite, grossular, titanite, and graphite. X-ray compositional maps and cathodoluminescence images highlight oscillatory zoning and skeletal textures in jadeite, omphacite and garnet in the matrix, suggesting a fast matrix precipitation under plausible disequilibrium conditions. CH4 and H2 are found in fluid inclusions in the jadeite grains. This feature suggests a potential link between the genesis of CH4 in the adjacent carbonate rocks and the brecciation event.EBSD analysis was performed on omphacitite clasts close to their borders, where omphacite grain size varies between a few microns and a maximum of 100 microns. Those omphacite grains display no crystallographic preferred orientation, abundant low angle boundaries and low (< 5°) internal lattice distortion. We interpret these textures as formed by pervasive and diffuse micro-fracturing related to the brecciation occurring at high pore fluid pressure, reaching sub-lithostatic values. This study suggests that at high-pressure conditions in subduction zones, the genesis and migration of hydrocarbon-bearing fluids can trigger fracturing in adjacent lithotypes. 1 Giuntoli, F., Vitale Brovarone, A., Menegon, L., 2020. Feedback between high-pressure genesis of abiotic methane and strain localization in subducted carbonate rocks. Sci. Rep. 10, 9848. https://doi.org/10.1038/s41598-020-66640-3 This work is part of project that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 864045).  
Evidence for electrostatic and Alfvénic accelerations in the Europa footprint tail revealed by Juno in-situ measurements
Authors: Rabia Jonas , Hue Vincent , Szalay Jamey R. , André Nicolas , Nénon Quentin , Blanc Michel , Allegrini Frederic , Bolton Scott J. , Connerney Jack E.P. , Ebert Robert W. , Greathouse Thomas K. , Louarn Philippe , Mura Alessandro , Penou Emmanuel , Sulaiman Ali H.
Published: February 2023

Moon-magnetosphere interactions result from the encounter between a magnetospheric plasma flow and moons, which act as obstacles to the plasma flow. In the Jovian magnetosphere, the Galilean moons orbit with a Keplerian velocity much slower than the plasma velocity, driven in near corotation by the planetary magnetic field. Therefore, they disturb the magnetospheric plasma flow, which in turn generates Alfvén waves in their close environments. These waves propagate along the magnetic field lines, accelerating particles and triggering auroral emissions in the giant planet atmosphere.Since August 2016, the Juno mission has made it possible to characterize in-situ the moon-magnetosphere interactions. Several crossings of the flux tubes connected to the orbits of the Galilean moons have been reported, revealing a diversity of particle properties and acceleration processes. However, Europa-magnetosphere interaction, whose remote and in-situ signatures are weaker and more difficult to identify than those of Io, remain poorly known.We characterize the precipitating electrons accelerated in the Europa-magnetosphere interaction by analyzing in-situ measurements and remote sensing observations recorded during 10 crossings of the flux tubes connected to Europa's auroral footprint tail by Juno. The electron downward energy flux exhibits an exponential decay as a function of down-tail distance from Europa's main auroral spot, with an e-folding factor of 7.2°. Electrons are accelerated at energies between 0.3 and 25 keV, with a characteristic energy that decreases down‐tail. We show that in the near tail (∆λFrac < 6°), acceleration is due, at least in part, to electrostatic processes while in the far tail (∆λFrac > 6°) broadband energy spectra are evidence for Alfvénic acceleration. The size of the interaction region at the equator is estimated to be 4.5 Europa radii, consistent with previous estimates based on theory and UV observations.
Fusion of a Statistical Emulator and Climate Model to Embed High Resolution Variability into a Coarse Resolution Climate Simulation
Authors: Giles Daniel , Morcrette Cyril , Guillas Serge
Published: February 2023

High resolution global climate simulations are computationally intractable due to the integration over long time scales. Therefore coarse spatial resolution models are used. One of the known failings of current climate simulations is the underrepresentation of cloud formation, which is largely due to the disparity in the spatial scale of the model and the underlying cloud generating physical processes. In this work emphasis has been placed on fusing an emulator with a climate model so as to embed high resolution variability into a coarse resolution climate model - with the aim of improving the representation of convective cloud formation.

A multi-output Gaussian Process (MOGP) is trained on high resolution Unified Model (UM) runs to predict the variability on the temperature and specific humidity fields. A proof of concept study has been carried out where the trained MOGP model is then coupled in-situ with a simplified Atmospheric General Circulation Model (AGCM) named SPEEDY. The mean profiles of the SPEEDY model are perturbed at each timestep according to the predicted high resolution informed variability. The climate statistics from the fused model are then compared to the pure model run. Improvements in the precipitation, outgoing longwave and shortwave radiation patterns are observed.
Investigation of the Physical Processes Involved in GNSS Amplitude Scintillations at High Latitude: A Case Study
Authors: D'Angelo Giulia , Piersanti Mirko , Pignalberi Alessio , Coco Igino , De Michelis Paola , Tozzi Roberta , Pezzopane Michael , Alfonsi Lucilla , Cilliers Pierre , Ubertini Pietro
Published: February 2023

The storm onset on 7 September 2017, triggered several variations in the ionospheric electron density, causing severe phase fluctuations at polar latitudes in both hemispheres. In addition, although quite rare at high latitudes, clear amplitude scintillations were recorded by two Global Navigation Satellite System receivers during the main phase of the storm. This work attempted to investigate the physical mechanisms triggering the observed amplitude scintillations, with the aim of identifying the conditions favouring such events. We investigated the ionospheric background and other conditions that prevailed when the irregularities formed and moved, following a multi-observations approach. Specifically, we combined information from scintillation parameters and recorded by multi-constellation (GPS, GLONASS and Galileo) receivers located at Concordia station (75.10°S, 123.35°E) and SANAE IV base (71.67°S, 2.84°W), with measurements acquired by the Special Sensor Ultraviolet Spectrographic Imager on board the Defense Meteorological Satellite Program satellites, the Super Dual Auroral Radar Network, the Swarm constellation and ground-based magnetometers. Besides confirming the high degree of complexity of the ionospheric dynamics, our multi-instrument observation identified the physical conditions that likely favour the occurrence of amplitude scintillations at high latitudes. Results suggest that the necessary conditions for the observation of this type of scintillation in high-latitude regions are high levels of ionization and a strong variability of plasma dynamics. Both of these conditions are typically featured during high solar activity.
Sn attenuation characteristics in the Bhutan Himalaya.
Authors: Sarkar Sukanta , Singh Chandrani , Tiwari Ashwani Kant , Kumar M Ravi , Dubey Arun Kumar , Dutta Abhisek , Kumar Gaurav , Singh Arun
Published: February 2023

Seismic attenuation structure of the uppermost mantle is investigated using Sn waves in Bhutan Himalaya. Sn phase is the uppermost mantle-refractedphase, which travels with a velocity of 4.3 - 4.7 km/s. Visual inspection of all the seismograms are conducted to examine the efficient, inefficient and blocked paths in the region. The inefficient, and blocked S n phases are mainly observed from the western side of our study region. Sn attenuation is determined using the two-station Methodology (TSM ). We have generated 460 station pairs from 1539 seismograms with magnitude ≥ 4 within an epicentral distance of 200 - 1650 km recorded at 38 seismic stations. Furthermore, a 2D Sn Q model is produced to understand the upper mantle rheology of the area. The central part shows a low Q (≤100) value while high Q dominates in northern and western parts of Bhutan Himalaya. The overall results correlate well with the tectonic setting beneath the study region. A comparison study is also made with the adjacent Arunachal Himalaya for better understanding.
Mesosphere and Lower Thermosphere wind speed determination using data from the radio forward scatter BRAMS network
Authors: Lamy Hervé , Balis Joachim
Published: February 2023

BRAMS (Belgian RAdio Meteor Stations) is a network using forward scatter of radio waves on ionized meteor trails to study meteoroids. It is made of a dedicated transmitter and of 44 receiving stations located in or near Belgium. The transmitter emits a circularly polarized CW radio wave with no modulation at a frequency of 49.97 MHz and with a power of 130 W. Each receiving station uses a 3-element zenith pointing Yagi antenna. The first stations used analog ICOM-R75 receivers and a PC. Since 2018, new improved stations have been installed using digital RSP2 receivers, a GPSDO and a Raspberry Pi, providing better dynamic, sensitivity and stability. Recently, several methods have been developed to reconstruct trajectories from meteor echoes recorded at several BRAMS stations. These methods rely on time delays between meteor echoes, pre-t0 phase measurements, and sometimes information from a radio interferometer, or a combination of all the methods. This has opened the possibility to use the BRAMS network to determine the Mesosphere and Lower Thermosphere (MLT) wind speeds using data coming from a large number of meteor echoes.In this work, we will present the status of the BRAMS network and discuss how BRAMS data can be used to determine MLT wind speeds.  Using a forward scatter system with a very large number of stations allows to increase the number of detections, to increase the altitudinal coverage, and to relax the homogeneity assumption.  Simulations will be considered to estimate the impact of the meteoroid trajectory reconstruction uncertainties (in particular the uncertainty on altitude of the specular reflection point) on the wind speeds retrieval.  We will discuss which temporal and spatial resolutions of the MLT wind field measurements can be achieved.  We will finally discuss several upcoming upgrades of the network and their potential impact on this work.  
Characterization of Tropical Tropopause Layer clouds combining balloon-borne and space-borne observations
Authors: Lesigne Thomas , Ravetta Francois , Podglajen Aurélien , Tran Dung , Bureau Jérôme , Mariage Vincent , Pelon Jacques , Hauchecorne Alain
Published: February 2023

Tropical Tropopause Layer clouds have a significant impact on the Earth's radiative budget and regulate the amount of water vapor entering the stratosphere. They are a key component of the climate system but their observation is still challenging. The Strateole-2 project aims at a  better understanding of dynamical, transport, and processes in the Tropical Tropopause Layer (TTL) using long-duration super-pressure balloons flying for several months in the lower stratosphere along the equator belt. From October 2021 to late January 2022, three microlidars flew onboard stratospheric balloons, slowly drifting just a few kilometers above the clouds. These observations have unprecedented sensitivity to thin cirrus and provide a fine scale description of cloudy structures both in time and space. Statistical comparisons with spaceborne lidar CALIOP are discussed, highlighting the unique ability of the microlidar to detect optically thin clouds. The modulation of outgoing longwave radiation by tropical clouds is also investigated using the balloon-borne observations. 
Data driven stochastic primitive equations with dynamic modes decomposition
Authors: Tucciarone Francesco , Mémin Etienne , Li Long
Published: February 2023

The full numerical resolution of planetary flows, with the complex interdependence of mesoscale and sub-mesoscale dynamics that characterize such large scale circulation, is beyond reach with nowadays technology. When performing a numerical simulation of the ocean or the atmosphere, great care must be put in the choice of the parametrization of all those scales that are too small to be efficiently resolved.This work investigates the benefits of a stochastic decomposition of the Lagrangian trajectory into a smooth-in-time large scale velocity and a random fast-evolving uncorrelated part, ideally accounting for mesoscale and submesoscale processes. This approach, named Location Uncertainty (LU) [1], is built upon a stochastic version of the Reynolds Transport Theorem allowing us to cast the classical physical conservation laws into this scale-separated framework. This framework has been proven to be successful in several large-scale models for ocean dynamics [2,3,4,5].The derivation and implementation (within the community model NEMO, https://www.nemo-ocean.eu) of the hydrostatic primitive equations in this stochastic framework has been outlined in [6] and it is tested in this work with a novel data-driven approach based on dynamical mode decomposition [7]. The flow prediction in an idealized double-gyre configuration is shown to be improved by this stochastic contribution.[1], E. Mémin Fluid flow dynamics under location uncertainty,(2014), Geophysical & Astrophysical Fluid Dynamics, 108, 2, 119–146.[1] W. Bauer, P. Chandramouli, B. Chapron, L. Li, and E. Mémin. Deciphering therole of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach. Journal of Physical Oceanography, 50(4):983-1003, 2020.[2] W. Bauer, P. Chandramouli, L. Li, and E. Mémin. Stochastic representation ofmesoscale eddy effects in coarse-resolution barotropic models. Ocean Modelling, 151:101646, 2020.[3] Rüdiger Brecht, Long Li, Werner Bauer and Etienne Mémin. Rotating ShallowWater Flow Under Location Uncertainty With a Structure-Preserving Discretization. Journal of Advances in Modeling Earth Systems, 13, 2021MS002492.[5] V. Resseguier, L. Li, G. Jouan, P. Dérian, E. Mémin, B. Chapron, (2021), New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics, Archives of Computational Methods in Engineering.[6] F.L. Tucciarone, E. Mémin, L. Li, (2022), Primitive Equations Under Location Uncertainty: Analytical Description and Model Development, Stochastic Transport in Upper Ocean Dynamics, Springer.[7] L. Li, E. Mémin, G. Tissot,  Stochastic Parameterization with Dynamic Mode Decomposition, Stochastic Transport in Upper Ocean Dynamics, Springer.
Lateral variation of body wave attenuation in crust of Bhutan Himalaya
Authors: Dutta Abhisek , Singh Chandrani
Published: February 2023

We have studied the spatial variation of body wave (P and S wave) attenuation properties in crust of Bhutan region using small magnitude (2-4 ML) earthquakes. We have used continuous waveform data of 385 local earthquakes recorded by the GANSSER network operated by Swiss Seismological Service at ETH Zurich. Initially, the attenuation quality factors (Qp, Qs) have been estimated using Extended Coda Normalization method for five different frequencies (1.5, 3,6,12,18 Hz) at each station, as well as for two zones (eastern and western Bhutan). Q0 (Q value at 1 Hz) values are found to vary between 21-102 and 43-191 for P wave and S wave respectively for the whole region. We observe Qp = (72 ± 6)f(0.94 ± 0.06) and Qs = (104 ± 6)f(1.03 ± 0.05) for the eastern Bhutan whereas for the western part, Qp = (28 ± 1)f(1.41 ± 0.03) and Qs = (90 ± 5)f(1.07 ± 0.05) are found. Overall, frequency dependent coefficient values indicate the strong frequency dependent nature of Bhutan Himalaya. The spatial maps of Q0 for both waves suggest P-wave attenuates faster in the crust of western Bhutan compared to the eastern part. Paro, located in eastern Bhutan, shows comparatively high attenuation for both P and S waves. Further, azimuthal variation of attenuation properties around each station has been evaluated. The observed results are in good agreement with the tectonic settings of the region. The estimated attenuation properties are well comparable with the tectonically active regions in the world.
The importance of a multi-temporal approach to assess climate change impacts in Northern Italian agriculture
Authors: Straffelini Eugenio , Tarolli Paolo
Published: February 2023

The territory of north-eastern Italy, crossed by the Po River, which flows eastward into the Adriatic Sea, is home to flourishing agricultural production. The area is among Europe's most important rural regions and is crucial for food production. However, the sector is facing the impact of climate change. Among the most worrying phenomena is an increase in the frequency of more severe and longer drought periods, leading to progressively arid climatic conditions. The summer of 2022 was one of the most critical times on record, with the combination of extreme temperatures and severe water shortages. The effects severely impacted agriculture, with crop loss, irrigation problems, and saltwater intrusion into the Po River delta. Emerging multi-temporal satellite remote sensing technologies and the application of big data-based algorithms allow in-depth knowledge of phenomena occurring on Earth and the subsequent research of mitigation solutions. Specifically, monitoring the impacts of extreme drought in the region can be useful in understanding which areas are most at risk in the short term, while the use of future climate models can guide more resilient agricultural management in the future. This research first proposes the application of multi-temporal MODIS satellite indices to assess the agricultural drought that affected north-eastern Italy in the summer months of 2022 and secondly analyses the possible traces of climatic aridification. In addition, we present a study on the relationship between agricultural lands and current & future climates, carried out using high-resolution climate zone maps (RCP8.5 scenario). The aim is to understand the potential future climate in the currently cultivated fields. Mapping present and future critical areas and knowing which farming systems are most at risk due to climate change can be valuable information for managing agricultural assets under the threat of climate change. Acknowledgements - This study was carried out within the Agritech National Research Center and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022).
Development, intercomparison and evaluation of an improved mechanism for the oxidation of dimethyl sulfide
Authors: Archibald Alexander , Cala Ben , Archer-Nicholls Scott , Abraham N. Luke , Griffiths Paul , Jacob Lorrie , Shin Matthew , Revell Laura , Woodhouse Matthew
Published: February 2023

Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean. The oxidation of DMS is important for global climate through the role DMS plays in setting the sulfate aerosol background in the troposphere. However, the mechanisms of DMS oxidation are very complex and have proved elusive to accurately determine in spite of decades of research. As a result the representation of DMS oxidation in global chemistry-climate models is often greatly simplified. Recent field observations and laboratory studies have prompted renewed efforts in constraining the uncertainty in the oxidation mechanism of DMS as incorporated in global chemistry-climate models. Here we build on recent laboratory and observational evidence and develop a new DMS mechanism for inclusion in the UKCA chemistry-climate model. We compare our new mechanism to the existing UKCA mechanism and to a range of recently developed mechanisms reported in the literature through a series of global and box model experiments. Our box model experiments highlight that there is significant variance in simulated secondary oxidation products of DMS across mechanisms used in the literature, with divergence in the sensitivity of these products to temperature exhibited. Our global model studies show that our updated and improved DMS scheme performs better than the current scheme when compared against observations. However, sensitivity studies underscore the need for further laboratory and observational constraints.
Different aspects of hydrological forecast assessment in Slovakia
Authors: Hlaváčiková Hana , Hrušková Kateřina , Kopáčiková Eva , Mikuličková Michaela , Zvolenský Marcel , Shenga Zinaw , Lešková Danica
Published: February 2023

A well-configured, verified hydrological operational forecasting system is an invaluable tool for hydrological forecasting and warning services. Target users of such a service can be water managers, power generation planning, navigation, civil protection, and the public, whose priority is to obtain the best possible forecast for their area of interest. This was one of the reasons why SHMU proceeded to a more complex assessment of hydrological forecasts.The main objective of the assessment was to analyse the uncertainties that significantly affect the quality of the forecast itself. The evaluation was conducted for 47 selected water-gauging profiles. It showed that in Slovak physical-geographical conditions, the precipitation data (measured and predicted) and the configuration of the hydrological model are the most significant sources of uncertainties. Forcing data for hydrological forecasts come from the deterministic ALADIN/SHMU model with 4.5 km resolution, generated 4 times per day with hourly time-step and lead time 69 hours. The HBV model efficiency was tested on a total of 138 forecast profiles during the period 08/2016 – 12/2020. The input data used was precipitation from a combined radar product (qPrec) with 1 km resolution, which also enters the models in operation. Model performance was expressed by NSE and KGE statistics as well as visual inspection of the hydrographs. It showed very good model simulation results for most of the catchments. A weak point was the simulation and forecast of peak flows, which the model underestimated in many cases. It was therefore necessary to proceed to a more detailed analysis of the precipitation input, both measured and predicted, in relation to the predicted flows. Monthly precipitation totals and for selected catchments also daily ones were analysed and feedback was sent to the precipitation data providers for hydrological models. Monthly precipitation totals were compared with totals obtained from spatial interpolation of 568 rain gauge stations in a GIS environment. From these comparisons, systematic errors are visible as well as their temporal evolution for the specific catchments. Such analyses are not a routine part of hydrological forecasting systems.The work also includes a quantification of the uncertainty of the meteorological forecast and hydrological model separately expressed for different forecast lead times for a specific forecast profile. In the future, we would like to apply the methodology used for other profiles in order to detect possible systematic errors affecting the quality of the hydrological forecast.This work was supported by the Slovak Research and Development Agency under the Contract no. APVV-19-0340.
Effects of Cumulus and Radiation Parameterization on Summer Surface Air Temperature over Eastern China
Authors: Gao Zhibo , Yan Xiaodong , Zhao Chuanfeng , Guo Yan
Published: February 2023

Cloud-radiation process has strong impacts on surface air temperature (SAT). Using the Weather Research and Forecasting (WRF) model, this study investigates the effects of cumulus and radiation parameterization on SAT simulation over Eastern China (EC) during the summer season from 2001 to 2020. Four experiments are performed at a 30 km resolution using the combination of two cumulus schemes (KF and KF-CUP) and two radiation schemes (CAM and RRTMG). The results indicate that the KF and RRTMG scheme can produce warmer SAT than KF-CUP and CAM, respectively. By decomposing the differences in SAT simulation, it is found that KF and RRTMG have greater surface downward shortwave radiation (DSR), and the DSR shows a significant positive correlation with SAT in most parts of EC. Further analysis reveals that low-level cloud (LC) can strongly reflect the DSR, and the LC fraction (LCF) of KF and RRTMG is less than that of KF-CUP and CAM, respectively. The reason for this phenomenon is that the sub-grid cumulus heating rate is higher in KF and RRTMG, resulting in their higher air temperature (T) and greater differences between T and dew point (Td), which is not conducive to the formation of large-scale stratiform cloud and the increase of LCF. As a result, KF and RRTMG have more DSR and higher SAT than KF-CUP and CAM, respectively. The same mechanism can also explain the differences in the sub-seasonal cycle simulations between the four experiments. By comparing the SAT error in each subregion, this study can also provide a reference for future dynamic downscaling over the EC region.
Forecasting southward pointing magnetic fields in solar coronal mass ejections
Authors: Möstl Christian , Amerstorfer Ute , Rüdisser Hannah T. , Weiss Andreas J. , Amerstorfer Tanja , Bauer Maike , Davies Emma E. , Bailey Rachel L. , Reiss Martin A.
Published: February 2023

The problem of forecasting southward pointing magnetic fields in coronal mass ejections (CMEs) is closely tied to our ability to measure their magnetic field configuration between the Sun and 1 AU. I will review some of the ideas that have been developed to tackle this problem, from using solar proxies, heliospheric images, Faraday rotation and measuring the in situ magnetic field near the Sun Earth-line. Another way to make progress is to use the L1 data as boundary conditions for fast ensemble simulations, focusing on the flux rope parts inside CMEs. However, for any type of modeling and forecasting we need to better understand the global magnetic structure and shape of CME flux ropes from multi-spacecraft observations, now delivered by spacecraft such as Parker Solar Probe, Solar Orbiter, BepiColombo, STEREO-Ahead and Wind, ACE or DSCOVR. In the future, the PUNCH mission will allow for the first time to extract 3D information from heliospheric images, forming another trailblazer towards developing models for ESA's Vigil mission, and setting the stage for possible interplanetary fleets of small spacecraft.
Structurally-constrained FD-EMI data inversion using a Minimum Gradient Support (MGS) regularization
Authors: Klose Tim , Guillemoteau Julien , Vignoli Giulio , Koyan Philipp , Walter Judith , Herrmann Andreas , Tronicke Jens
Published: February 2023

In geophysical data inversion, one way to decrease the non-uniqueness of the solutions is to incorporate structural constraints. Such structural constraints are typically derived from collocated geophysical data, which are more sensitive to subsurface structures and parameter contrasts than the to-be-inverted data. When using a smooth regularization operator, a straightforward approach is to reduce the local weight of the smoothness constraints in model regions where we expect an interface. However, when using such an inversion approach, the capability to reconstruct a sharp interface relies only on the structural a priori information; i.e., model areas where no structural a priori information is available are solely controlled by the standard smoothness constraints. Therefore, this approach is not optimal in practice, as the structural a priori information is often not complete.In this study, we evaluate a structurally-constrained inversion approach based on the Minimum Gradient Support (MGS) regularization, which is capable to promote sharp interfaces also in areas where no structural a priori information is explicitly specified. We test and evaluate this regularization approach for the inversion of frequency-domain electromagnetic induction (FD-EMI) data, where we use a constant-offset 3D GPR data set to derive structural a priori information. Our field data set covers an area of about 120 m x 50 m and has been collected at a field site in Kremmen, Germany, to explore peat deposits. Our results demonstrate that the proposed structurally-constrained inversion approach helps in finding a reliable subsurface structures (e.g., peat thickness) as well as a reliable reconstruction of the subsurface electrical conductivity distribution within the peat formation (e.g., related to varying degrees of peat decomposition) and within the sandy substratum.
Post-drought nitrate mobilization in German catchments
Authors: Saavedra Felipe , Musolff Andreas , Von Freiberg Jana , Merz Ralf , Knoll Kay , Müller Christin , Brunner Manuela , Tarasova Larisa
Published: February 2023

Nitrate excess in rivers is caused by anthropogenic nitrogen sources, such as agriculture and wastewater. Diffuse sources stemming from agricultural fertilization can remain in the soil for long periods of time as a legacy and are mobilized through hydrological pathways that connect sources with rivers. Previous studies show that drought periods can increase nitrogen stored in the soil due to lower nitrate transport to streams and less nitrate uptake by plants due to dry conditions. This accumulation of nitrogen during drought and its subsequent transport under wet conditions during the post-drought period can result in high nitrate concentrations in rivers.In our study, we analyze the nitrate response of 190 German rivers during hydrological post-drought conditions from 1978 to 2019. We define droughts as periods with more than 30 consecutive days of discharge deficit using a variable threshold method and post-droughts as 100-day periods following the termination of a drought. We particularly focus on post-drought periods in the winter season that display the most pronounced concentration anomalies. Our results show that during the winter post-drought period, 66% of the catchments export higher nitrate concentrations compared to non-drought conditions, with 19% of the catchments exporting significantly higher nitrate concentrations (Kruskal-Wallis test, p-value<0.05). Catchments that exhibit a significant increase in nitrate concentrations during winter post-drought periods tend to be characterized by higher annual precipitation and shallower aquifers, indicating that fast hydrological transport could be a key factor in the winter post-drought delivery of nitrate excess. A projected increase in the frequency of severe droughts due to climate change could lead to more frequent post-drought episodes with high nitrate concentrations in the future. Understanding the main drivers of post-drought transport of nitrate across catchments is crucial for focusing management efforts efficiently.
A Bayesian decision framework to support flood anticipatory actions in the urban data scarce city of Alexandria, Egypt
Authors: Young Adele , Bhattacharya Biswa , Zevenbergen Chris
Published: February 2023

Ensemble prediction systems (EPS) have been proposed to quantify uncertainty in forecasts, but to what extent they are useful for supporting flood anticipatory actions in an urban data-scarce city has not been fully explored. This research uses a Bayesian decision theory framework to support sequential decisions for reducing flood impacts. The predictive information is derived from probability distributions of flood depth simulated from a coupled ensemble Weather Research and Forecasting (WRF) and hydrodynamic MIKE urban inundation model. A damage function is used to value user actions and expected damages. Posterior probabilities are computed using prior probabilities and expected damages to select an action which minimises the expected losses.The analysis is done for the Egyptian coastal city of Alexandria, which experiences extreme rainfall and pluvial flooding from winter storms resulting in disruptions, damages and loss of lives. The decision framework supports anticipatory actions which can be taken 12-72 hours before an event. These include cleaning drains, dispatching pump trucks to critical flood locations before events, and proactive pumping to increase storage.Results suggest the use of a probabilistic decision framework can help support mitigating actions and reduce the occurrence of false and missed alarms. However, it depends on the combination of event intensity and probability (e.g. high intensity, low probability) the specific action and the loss function used. This approach helps decision-makers understand the value of probabilistic forecasts and models to trigger actions for improved decision support.
Climate Resilience of IoT devices: A user survey perspective
Authors: Zhunissova Dinara
Published: February 2023

Climate Resilience of IoT devices: A user survey perspectiveClimate change is due to have significant impacts across Central Asia. At the same time, IoT is being used to construct many new industries and provide new ways of managing logistics across existing sectors. For example, Climate change will affect Central Asia's agricultural production which will occur alongside increased frequency of drought, water scarcity, and soil salinization, which will cause food insecurity in the region.  How do we move towards secure management of systems that rely on IoT in a changing climate?In this research I want to quantifying potential risks to IoT systems, and their connected end points, according to Climate resilience. To do this our work examines concepts and theories from a variety of fields to demonstrate how it could help transport companies and organizations prevent risk in extreme weather conditions.First, in order to understand risk perception and mitigation for stakeholders, an online survey was created and sent across both public and private sector organisations in Kazakhstan. By delving into the outcomes of this survey, we can better understand perceived risks and map processes implemented in these organisations to potential impacts. In this short presentation we will review those outcomes and discuss future strategies to enable secure resilience.  
An EOSC-enabled Data Space environment for the climate community
Authors: Antonio Fabrizio , Elia Donatello , Levavasseur Guillaume , Ben Nasser Atef , Nassisi Paola , D'Anca Alessandro , Nuzzo Alessandra , Fiore Sandro , Joussaume Sylvie , Aloisio Giovanni
Published: February 2023

The exponential increase in data volumes and complexities is causing a radical change in the scientific discovery process in several domains, including climate science. This affects the different stages of the data lifecycle, thus posing significant data management challenges in terms of data archiving, access, analysis, visualization, and sharing. The data space concept can support scientists' workflow and simplify the process towards a more FAIR use of data.In the context of the European Open Science Cloud (EOSC) initiative launched by the European Commission, the ENES Data Space (EDS) represents a domain-specific implementation of the data space concept. The service, developed in the frame of the EGI-ACE project, aims to provide an open, scalable, cloud-enabled data science environment for climate data analysis on top of the EOSC Compute Platform. It is accessible in the European Open Science Cloud (EOSC) through the EOSC Catalogue and Marketplace (https://marketplace.eosc-portal.eu/services/enes-data-space) and it also provides a web portal (https://enesdataspace.vm.fedcloud.eu) including information, tutorials and training materials on how to get started with its main features. The EDS integrates into a single environment ready-to-use climate datasets, compute resources and tools, all made available through the Jupyter interface, with the aim of supporting the overall scientific data processing workflow.  Specifically, the data store linked to the ENES Data Space provides access to a multi-terabyte set of variable-centric collections from large-scale global climate experiments.  The data pool consists of a mirrored subset of CMIP (Coupled Model Intercomparison Project) datasets from the ESGF (Earth System Grid Federation) federated data archive, collected and kept synchronized with the remote copies by using the Synda tool developed within the scope of the IS-ENES3 H2020 project. Community-based, open source frameworks (e.g., Ophidia) and libraries from the Python ecosystem provide the capabilities for data access, analysis and visualisation. Results  and experiment definitions (i.e., Jupyter Notebooks) can be easily shared among users promoting data sharing and application re-use towards a more Open Science approach. An overview of the data space capabilities along with the key aspects in terms of data management will be presented in this work.
An improved stacking ensemble network considering the proximity effects of spatiotemporal dependency for landslide predictive modeling
Authors: Zhao Zheng , Lan Hengxing , Li Langping , Wu Yuming
Published: February 2023

The consideration in proximity effects of spatiotemporal dependency on statistical landslide susceptibility modeling (LSM) is still insufficient and problematic. How to quantify the proximity effects and effectively integrate the temporal characteristic of historical landslide occurrence into start-of-the-art machine learning (ML) methods instead of assuming that the occurrence of historical landslides is time-independent, which remains should be considered. In this paper, an improved stacking ensemble network considering the proximity effects of spatiotemporal dependency was proposed for LSM. Specifically, we used the space-time clustering method to quantify the proximity effects of spatiotemporal on the landslide occurrence and scientifically split the landslide inventory with long time series into eight-time slices. Furthermore, a stacking ensemble technique combined four classifiers in an aggregated way to train the eight sub-models based on eight-time slices and long short-term memory (LSTM) as a base classifier was used to produce reliable results by aggregating the above eight sub-models in a weighted average way. The experimental result shows that the proposed model outperformed than above sub-models and considered the full-timescales model in terms of statistical indexes, LSM, and probability distribution, respectively. We also found that the robustness and prediction accuracy of the model will increase as the training dataset increase. Overall, the novel approach highlights the need to consider the proximity effects of spatiotemporal dependency in LSM and can lead to correct management decisions in landslide prevention and mitigation.
Increasing the spatial resolution of wave fields when the amount of available instruments is limited
Authors: Padilla Enrique M. , Cao Rui , Callaghan Adrian H.
Published: February 2023

A relatively high spatial resolution is often desirable when capturing the spatial variability of evolving wave fields. Some of these situations where a high spatial resolution is needed may be, for example, studing the shape evolution of breaking waves, or studing the directional distribution of the energy of wind-wave spectra, where computing the frequency-wavenumber spectra is critically needed. In both cases, an ideal space-time representation of the wave field is the one whose spatial and time resolutions are high enough (∆x and ∆t being very small), or to some extend, comparable in relative terms (∆x/λ ≈ ∆t/T), i.e., ∆x and ∆t representing a tiny fraction of the characteristic wavelength (λ) and period (T), respectively. In this case, the wave field in the space-time domain looks like a continuous 2D function. However, reaching such high spatial resolutions is not very common in experimental or field works. In some cases, such high resolution is not needed. In some other cases, such high resolution is not possible due to unavoidable experimental, technical and cost constraints, and that results in a limited number of available instruments. To overcome this limitation, we present a relatively simple procedure called S-interp, which is freely available at https://github.com/EMPadilla/Sinterp. S-interp is to interpolate wave fields at spatial locations where no measurements are available. S-interp uses a Modified Akima cubic Hermite interpolation along points in the wave field that are in phase. The main hypothesis of S-interp is that the wave field follows a linear-like evolution along points being at the same phase. Therefore, along these points, differences between the interpolated and the actual wave fields are minimal. Some factors for these differences to rise are: (i) The spatial distribution of the instruments, (ii) the nonlinear effects that modify the wave geometry increasing its asymmetry and skewness and (iii) the interpolation method used. We assess the performance of S-interp by reconstructing missing areas of experimental non-breaking wave conditions, gathered in SIREN-NB data set. These are 33 non-breaking focused wave events designed using a NewWave-type spectra for peak periods ranging from 1.0 s to 1.7 s with a peak enhancement factor set to 2. The wave conditions are recorded by video cameras and the wave fields are measured by video-image detection. The experiments were conducted in the Wind-Wave-Current flume at the Hydrodynamics Lab - Imperial College London. Preliminary results suggest that S-interp seems to be more sensitive to the spacing between the instruments than to the nonlinear effects of the wave fields.
Urban heat maps in support of EU adaptation policy (u-MAP)
Authors: Lefebre Filip , Lauwaet Dirk , Souverijns Niels , Veldeman Nele
Published: February 2023

In this presentation, we will present and discuss a Destination Earth use case that intends to provide present and future high-resolution urban heat maps for cities across Europe to underpin and motivate urban climate adaptation measures that are being developed within the EU’s cohesion policy and the development of EU policies related to the urban environment.In recent years, climate change has been causing increasingly frequent and intense heatwaves in Europe.  Climate projections indicate that the population exposure to extreme heat will rise by more than an order of magnitude towards the end of the century. Cities are especially at risk because of the urban heat island phenomenon, which may cause a doubling in the annual number of heatwave days compared to rural areas.   Within the EU, large geographical disparities exist in present and future (projected) exposure to heat, cities and regions in South and Central Europe exhibiting a higher risk. The monitoring of such disparities is important for Europe’s cohesion policy, which aims to develop measures to assist the economic and social development of the EU’s less-favoured regions. While some monitoring of urban heat patterns has been achieved by means of thermal infrared remote sensing, this type of information does not allow to derive sectoral indicators; the high-resolution urban climate information required to do so is currently lacking.The urban heat maps will be generated by means of a physics-based urban climate model, UrbClim, nested within large-scale atmospheric output provided by the DestinE adaptation digital twin. 
Globally modelling explicit convection: how does it compare with the nested limited area model approach at high horizontal resolutions?
Authors: Macholl Joshua , Jones Richard , Lewis Huw
Published: February 2023

The difficulty to accurately represent atmospheric convection in numerical weather forecasts contributes to persistent biases in weather and climate simulations – particularly tropical precipitation. Convection-permitting global forecasts are an improvement on global models with parametrized convection schemes, however it is not yet clear whether they improve forecast skill to match or improve upon the current approach of nesting a convection-permitting high-resolution regional model inside a global model with parameterized convection. This is far less computationally expensive than running a global convection-permitting model.To test this, the Met Office is coordinating a UK K-scale project nesting high resolution (2.2 km) limited area models (LAMs) within global models that have between 5 and 10 km grid resolution. We compare these nested regional models with two different global simulations, run with parameterised and explicit convection science configurations. The 2.2 km resolution LAMs encompass a variety of domains focussing on both tropical land and ocean regions.Our current work seeks to investigate if and where we see differences in model evolution between the high-resolution nested LAM approach and the explicit convection global driving model.  We focus on an active MJO event in January 2018 where enhanced convection propagated across the Indian Ocean and impacted the Maritime continent. For high-impact events such as this, do we see a marked change in the model forecast when explicitly simulating convection globally rather than in a regional limited area model (as currently used in operational forecasts)? Further, are differences between the global convection permitting and LAM forecasts more pronounced over ocean-dominated regions where the amplitude of the diurnal cycle of convection is smaller?This talk will summarise our findings in the context of the wider K-scale project, evaluating how our recent work contributes to the development of more accurate weather forecasts.