bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of extracted ecological features of forests from multiple 3D technologies
Authors: Lines Emily , Flynn William , Grieve Stuart , Owen Harry , Ruiz-Benito Paloma
Published: February 2023

The recent explosion in availability of high resolution remote sensing technologies and, crucially, the tools to analyse the 3D data they produce is leading to substantial interest in using them for widespread forest structural monitoring. The level of detail contained in the entire 3D shape of trees, fully captured within these data, can generate a wide range of metrics of interest to ecologists, but the potential metrics of interest and their uncertainties have not been fully explored. In particular, the value of different technologies - whether passive or active sensors, and from the ground or the air - for accurately deriving different metrics is not well known. Working across a range of European forest ecosystems, we have constructed a unique 3D dataset of European forest structural properties from passive and active sensors. We segment individual trees from concurrent and co-located Structure from Motion photogrammetry (SfM) (passive sensor), and UAV LiDAR, and terrestrial laser scanning (active sensors) campaigns, and use these to compute tree structural metrics. We compare the ability of these different technologies to accurately measure key tree properties across a diversity gradient in multiple biomes.
When and where to measure soil gases: an optimization approach for time series and spatial information
Authors: Vargas Rodrigo , Le Huong
Published: February 2023

A fundamental question for any sampling design is identifying where and when to measure. Technological advances allow us to measure multiple greenhouse gases (GHGs) simultaneously, and now it is possible to provide complete GHG budgets from soils (i.e., CO2, CH4, and N2O fluxes). We present a data-driven method for identifying optimized samples from times series (1D approach) or spatial arrays (2D approach) of information on soil gases. The autocorrelated conditioned Latin Hypercube Sampling (acLHS) combines a conditioned Latin Hypercube (cLHS) to obtain a representative sample of the joint probability distribution function and an autocorrelation model to ensure a reproducible spatial or temporal dependency function (i.e., temporal or spatial variability). The results show a conflict between the convenience of simultaneously measuring multiple soil GHG fluxes at fixed time intervals (e.g., once or twice per month) and the intrinsic temporal variability in and patterns of different GHG fluxes. Furthermore, the acLHS is more efficient than other sampling methods (i.e., fixed sampling, cLHS) as it can better reproduce the joint probability distribution and the temporal or spatial variability of the variables of interest. We test this approach using time series and spatial arrays to evaluate the relationship between soil CO2 efflux and temperature. These results have implications for assessing gas fluxes from soils and consequently reduce uncertainty in the role of soils in biogeochemical cycles.
The Winter North Pacific Teleconnection in Response to ENSO and the MJO in Operational Subseasonal Forecasting Models Is Too Weak
Authors: Schwartz Chen , Garfinkel Chaim , Chen Wen , Li Yanjie , Yadav Priyanka , Domeisen Daniela I.V.
Published: February 2023

Teleconnection patterns associated with the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO) impact weather and climate phenomena in the Pacific–North American region and beyond, and therefore accurately simulating these teleconnections is of importance for seasonal and subseasonal forecasts. Systematic biases in boreal midwinter ENSO and MJO teleconnections are found in eight subseasonal to seasonal (S2S) forecast models over the Pacific–North America region. All models simulate an anomalous 500-hPa geopotential height response that is too weak. This overly weak response is associated with overly weak subtropical upper-level convergence and a too-weak Rossby wave source in most models, and in several models there is also a biased subtropical Pacific jet, which affects the propagation of Rossby waves. In addition to this overly weak response, all models also simulate ENSO teleconnections that reach too far poleward toward Alaska and northeastern Russia. The net effect is that these models likely underestimate the impacts associated with the MJO and ENSO over western North America, and suffer from a reduction in skill from what could be achieved.
Rift Initiation via Unstable Basal Crevasses
Authors: Coffey Niall , Lai Ching-Yao , Wang Yongji
Published: February 2023

Ice shelves, the floating extensions of ice sheets, can reduce the rate of sea level rise by buttressing the upstream grounded ice. However, calving, or the fracturing that creates icebergs, can cut out regions that were resisting flow, and allow for increased ice flux and thus sea level contribution. In this work, I focus on the transition from basal crevasses, or seawater-filled fractures on the bottom surface, to full thickness fractures called rifts. Using RACMO ice shelf surface temperatures and holding the ice-ocean interface at -2℃, I find good agreement between observed rifts on the Larsen C and Ross Ice Shelves and rifts predicted to evolve from basal crevasses through 2D Mode I Linear Elastic Fracture Mechanics (LEFM). I also explore the influence of ice shelf geometry in rift formation by solving the Shallow Shelf Approximation (SSA) equations for idealized ice shelves with COMSOL’s Finite Element Analysis software. Using the stress field outputs with LEFM’s rift initiation criteria, I find qualitative agreement in the rift orientation between the predicted unstable basal crevasses and the observed rifts on the left margin of Pine Island Ice Shelf.
Preferential flow in a long-term no-tillage experiment on a silt loam soil in Mediterranean conditions
Authors: Lampurlanes Jorge , Talukder Rasendra , Plaza-Bonilla Daniel , Cantero-Martínez Carlos , Wendroth Ole
Published: February 2023

Water flow throughout the soil allows and regulates life on the Earth's surface. Knowing where this flow mainly takes place (preferential flow) is critical i) to measure it appropriately, ii) to take advantage of it for a more efficient use of water. Soil management has great impact on soil hydrological properties and can have an effect at catchment scale, while knowing within plot variability can improve flow estimations at plot level. On a 22-year-old experiment comparing intensive (IT) and no-tillage (NT), soil hydrological properties were determined within (W-row) and between (B-row) crop rows several times along two cropping years (2018-19 and 2019-20) on undisturbed soil cores. Tillage significantly influenced soil water retention being higher under IT than NT in the wet range above -10 cm soil matric potential. The cause was a larger volume of mesopores (1000 to 300 µm in diameter) in IT. Despite that, hydraulic conductivity was significantly higher in NT in this range, especially because mesopores in NT revealed greater pore continuity than in IT. No differences in soil hydraulic conductivity were found at lower soil matric potentials. These results suggest that, although IT increases soil porosity creating new pores regularly, these pores are less interconnected than the long-standing pores created in NT by the roots and fauna activity. The lower hydraulic conductivity in IT can reduce infiltration and increase runoff losses resulting in less water available for crops.  The position with respect to the crop row (W-row or B-row), did not have an impact on soil water retention but on soil hydraulic conductivity, that was significantly higher under W-row than B-row above -10 cm H2O soil water potential. Although the volume of pores of different size classes did not differ between both row positions, continuity of macropores (>1000 µm) was significantly higher under W-row than B-row and tended to be higher W-row also for the other pore classes. The effect of the sowing slot, the growth of the plant roots, and the protective effect of the plant cover itself can explain the preferential flow pathway found W-row. The differences between flow regimes under different tillage systems found at the small scale highlight the importance of considering the site-specific management impacts on soil structure and pore geometry, as these will affect hydrological flow processes at the catchment scale. Differences between positions with respect to the plant row need to be considered to properly characterize hydrological flow phenomena in soils, even under the same management practices.
Multi-Soil-Layering, the Emerging Technology for Wastewater Treatment: Review, Bibliometric Analysis, and Future Directions
Authors: Sbahi Sofyan , Mandi Laila , Masunaga Tsugiyuki , Ouazzani Naaila , Hejja Abdessamad , Lahrouni Abderrahman
Published: February 2023

Due to its unique structure and excellent purification efficiency (e.g., 98% for organic matter and between 94 and 100% for nutrients), multi-soil-layering (MSL) has emerged as an efficient eco-friendly solution for wastewater treatment and environmental protection. Through infiltration-percolation, this soil-based technology allows pollutants to move from the MSL upper layers to the outlet while maintaining direct contact with its media, which helps in their removal via a variety of physical and biochemical mechanisms. This paper attempts to comprehensively evaluate the application of MSL technology and investigate its progress and efficacy since its emergence. Thus, it will attempt via a bibliometric analysis using the Web of Science database (from 1993 to 01/06/2022) related to MSL technology, to give a clear picture of the number of publications (70 studies), the most active academics, and countries (China with 27 studies), as well as collaborations and related topics. Furthermore, through hybrid combinations, pollutant removal processes, MSL effective media, and the key efficiency parameters, this paper review will seek to provide an overview of research that has developed and examined MSL since its inception. On the other hand, the current review will evaluate the modeling approaches used to explore MSL behavior in terms of pollutant removal and simulation of its performance (R2 > 90%). However, despite the increase in MSL publications in the past years (e.g., 13 studies in 2021), many studies are still needed to fill the knowledge gaps and urging challenges regarding this emerging technology. Thus, recommendations on improving the stability and sustainability of MSLs are highlighted.
The Merging of a Coronal Dimming with the Southern Polar Coronal Hole During Solar Orbiter’s First Perihelion
Authors: Ngampoopun Nawin , Long David , Baker Deborah , Green Lucie , Yardley Stephanie , James Alexander , To Andy
Published: February 2023

We report a partial filament eruption in the southern solar hemisphere that occurred on 18 March 2022 during the first science perihelion of Solar Orbiter. The filament erupted into a coronal mass ejection (CME), producing coronal dimmings at the footpoints of the erupting structure. The expanding dimming then merged with the adjacent southern polar coronal hole. This merging of two open magnetic structures is observationally rare and poorly understood. We use remote sensing data from multiple co-observing spacecraft to understand the physical processes during this merging event. The evolution of the merger is examined using Extreme-UltraViolet (EUV) images obtained from the instruments onboard the Solar Orbiter and Solar Dynamic Observatory spacecraft. The plasma dynamics are quantified using spectroscopic data obtained from the EUV Imaging Spectrometer onboard Hinode. The preliminary results show that the coronal hole and coronal dimming become indistinguishable from each other after the merging. Several plasma upflow regions were observed throughout the merging event, suggesting the opening of magnetic field lines. The brightening of bright points and coronal jets inside the merged region further imply ongoing reconnection processes. This work also has implications for the formation of coronal hole/open field regions and the origin of solar wind from coronal dimming and coronal hole boundaries.
Exo-Venus, Exo-Earth, Exo-Dead in the Trappist-1 System?
Authors: Way Michael
Published: February 2023

Since the discovery of the Trappist-1 system a number of studies have explored which of these planets are within the canonical habitable zone with Trappist-1e the most likely Exo-Earth-like of the bunch [e.g. 1,2,3,4]. At the same time they also tend to indicate that Trappist-1d is likely an exo-Venus.  Using the ROCKE-3D General Circulation Model [5] we investigate whether Trappist-1d is likely to be an Exo-Venus, an Exo-Earth, or is a bare rock (Exo-Dead). We apply our previous approach to understand the climate history of Venus [6] to explore Trappist-1d.[1] Wolf, E.T. (2017) ApJ 839:L1[2] Turbet et al. (2018) A&A 612, A86[3] Krissansen-Totton, J. and Fortney, J.J. (2022) PSJ 933:115[4] Kane, S.R. et al. (2021) AJ 161:53 [5] Way, M.J. et al. (2017) ApJS 213:12[6] Way, M.J. and Del Genio, A.D. (2020) JGR Planets, 125, e2019JE00627
Improving Platform Magnetometer Measurements Using Physics-informed Neural Networks
Authors: Styp-Rekowski Kevin , Michaelis Ingo , Korte Monika , Stolle Claudia , Kao Odej
Published: February 2023

So-called platform magnetometers, mounted on a variety of non-dedicated satellites in Low-Earth orbit, are promising instruments to increase the spatiotemporal coverage of space-based measurements of the Earth’s magnetic field. However, these instruments often need to be calibrated to ensure a scientific accuracy and usability of the data they collect. To do this, it is important to gather information about the satellite to correct artificial disturbances caused by other payload systems as well as other influencing properties. In the past, we demonstrated that a Machine Learning-based calibration achieves competitive results. By using machine learning techniques, the magnetometer signal can be adapted to account for artificial disturbances and the proposed non-linear regression method can automatically identify relevant features and their crosstalk, enabling the use of a wider range of inputs. This reduces the analytical work required for the calibration of platform magnetometers, resulting in faster, more precise, and easily accessible magnetic datasets from non-dedicated missions. The calibrated datasets are made publicly available.In this work, we propose an extension for the known approach by incorporating the physical Biot-Savart formula into a neural network, which results in a physics-informed neural network. This improves the modeling and correction of the impact of current-induced artificial magnetic fields on the satellite and its magnetic measurements. In addition, the Average Magnetic field and Polar current System (AMPS) model is combined with the CHAOS-7 model, improving the reference model of the calibration, especially for the polar regions. This extended approach is applied to the GOCE and GRACE-FO satellite missions and their respective measurements. In the future, the underlying software shall be published and applied to a wider variety of satellites to improve the accuracy of their platform magnetometer measurements. By making this tool publicly available, we hope to enable other satellite operators to calibrate their instruments, improve the quality of their data, and make additional data available to the scientific community.
Estimating flows for hydropower: leveraging value from national scale hydrological modelling
Authors: Quinn Nevil Wyndham , Horswell Michael , Wyrill Declan
Published: February 2023

National-scale estimates of flow for determining hydropower suitability are invariably dependant on some form of the Drainage Area Ratio (DAR) method, where flows at a point of interest for hydropower are assumed to be a proportion of flows measured elsewhere in the catchment, based on a fixed ratio of respective catchment areas. This method is widely used globally.Recent UK national-scale modelling, using a variety of models, has established a significant set of reconstructed daily flows for many locations (G2G model: 260 catchments (flows: 1891-2015); GR4J model: 303 catchments (flows: 1891-2015); Decipher model: 1366 catchments (flows: 1962-2015)). These reconstructed flows supplement the national set of flow observations maintained in the UK National River Flow Archive but have the advantage that in many cases reconstructed timeseries cover a longer period than observed records. Although these are useful datasets, unless the site of hydropower interest approximates a gauged/modelled location, the problem of estimating flows at a different point, remains.The reconstructed datasets mentioned above include a national scale 1km x 1km grid of monthly flows generated by the G2G model (1891-2015). As these are gridded flows at high spatial resolution, it may be possible to estimate daily flows at a required location, based on a variable ratio of monthly flows for the respective locations – rather than a fixed area ratio.We propose and test a method for leveraging understanding from gridded monthly output for several locations within the Trent catchment. Daily flows at these locations are already known and were used for validation. We calculated monthly ratios of gridded flows at the sites of interest to those at a driver site, where daily flow is available. This variable monthly flow ratio was then applied to the daily flow at the driver location to estimate daily flow at the site of interest. Flow duration curves were compiled to compare flows using (i) the DAR method, (ii) the proposed flow factor method and (iii) the observed flows. Results generally indicated that the flow factor method provides good estimates (within 5 to 14% of recorded flow), and a significant improvement in flow estimation compared to the DAR method. However, for some locations, both methods performed poorly, and we explore possible reasons.
A New High-Resolution Ocean Reanalysis for the Baltic Sea: Insights into Ocean Dynamics
Authors: Korabel Vasily , Ringgaard Ida , Murawski Jens , Huess Vibeke , She Jun , Spruch Lena , Lindenthal Anja
Published: February 2023

Ocean reanalyses provide a valuable source of data for understanding the dynamics of the ocean, climate studies and practical applications. We introduce a new CMEMS high-resolution ocean reanalysis for the Baltic Sea for the period from 1993 to 2021. The reanalysis is an upgrade of the existing CMEMS products BALTICSEA_REANALYSIS_PHY_003_011 and BALTICSEA_REANALYSIS_BIO_003_012 and introduces numerous changes including higher horizontal resolution, approximately 1.9 km, a new versions of ocean, ice and biogeochemical models, and a new data assimilation scheme.We have analyzed the reanalysis data to assess the performance of the new reanalyses focusing on the ocean dynamics. We found that the high resolution of the reanalysis allowed us to detect finer-scale features in the data, such as mesoscale eddies, that were not apparent in lower resolution dataset as well as improve the ocean currents.We also used the reanalysis to study the occurrence and evolution of salt water inflows from the North Sea. Our results suggest that the high resolution of the reanalysis enables more accurate predictions of these events.Overall, our study demonstrates the utility of the new high-resolution ocean reanalysis for understanding the dynamics of the Baltic Sea and improving our ability produce a physically consistent combination of model and observations.
A case study of two simultaneous extreme aerosol events in the Mediterranean: The Mount Etna series of eruptions and major Saharan dust event in February 202
Authors: Sellitto Pasquale , Salerno Giuseppe , Corradini Stefano , Xueref-Remy Irène , Riandet Aurélie , Bellon Clémence , Khaykin Sergey , Ancellet Gerard , Lilli Simone , Welton Ellsworth J. , Boselli Antonella , Sannino Alessia , Cuesta Juan , Guermazi Henda , Eremenko Maxim , Merucci Luca , Stelitano Dario , Guerrieri Lorenzo , Legras Bernard
Published: February 2023

During the extended activity of Mount Etna volcano in February-April 2021, three distinct paroxysmal events took place from 21 to 26 February, which were associated with a very uncommon transport of the injected upper-tropospheric plumes towards the north. A major Saharan dust outbreak to central Europe occurred in the same period. Using a synergy of observations and modelling, we characterise the three-dimensional dispersion of these volcanic plumes and we disentangle their optical and radiative signature from the simultaneous Saharan dust transport. In the region of interest for our study, the volcanic and the dust plumes remain completely vertically-separated, thus facilitating the detection and spatiotemporal characterisation of the dispersion, properties and radiative impacts of these two different aerosol plumes, using vertically-resolved observations. With a satellite-based source inversion, we estimate the emitted sulphur dioxide (SO2) mass at an integrated value of 55 kt and plumes injections at up to 12 km altitudes, which qualifies this series as an extreme event for Mount Etna activity spectrum. Then, we combine Lagrangian dispersion modelling, initialised with measured temporally-resolved SO2 emission fluxes and altitudes, with satellite observations to track the dispersion of the individual volcanic and dust plumes. The general transport towards the north allowed the height-resolved downwind monitoring of the volcanic and dust plumes at selected observatories in France, Italy and Israel, using LiDARs and photometric aerosol observations. A specific effort has been dedicated to the characterisation of the volcanic aerosol plumes. Volcanic-specific aerosol optical depths in the visible spectral range ranging from about 0.004 to 0.03 and local daily average shortwave radiative forcing ranging from about -0.2 to -1.2 W/m2 (at the top of atmosphere) and from about -0.2 to -3.0 W/m2 (at the surface) are found. The composition (possible presence of ash), aerosol optical depth and radiative forcing of the volcanic plumes has a large inter- and intra-plume variability and thus depend strongly on the position of the sampled section of the plumes. The dust optical depth and radiative impact largely outweigh volcanic aerosols when the two plumes are co-located, for this event. This case study points at the complexity of the Mediterranean aerosol environment and pave the way to future studies at longer timescales, exploiting the available observational and modelling capabilities and their synergies.
Physics-based modeling of earthquakes in slow deforming areas: a case study from the Eastern Betic Fault System (SE Spain)
Authors: Herrero-Barbero Paula , Álvarez-Gómez José A. , Williams Charles , Villamor Pilar , Tsige Meaza , Insua-Arévalo Juan M. , Alonso-Henar Jorge , Martínez-Díaz José J.
Published: February 2023

The challenges in the characterization of slow-moving faults and the temporal limitations of the earthquake records in these regions complicate the seismic hazard assessment. The instrumental and historical seismic catalogs cover a short time period compared with the long recurrences between large destructive events in some faults. Paleoseismic evidence allows us to increase the time frame, but when field data is scarce, scattered or difficult to collect, numerical modeling provides us with an excellent tool to support the characterization of a fault system and its associated threat. Physics-based earthquake simulators overcome the limitations of actual earthquake catalogs and generate long-term synthetic seismicity. Recent numerical codes based on rate- and state-dependent friction allow the modeling of both the long-term seismic cycle deformation and the short-term rupture based on quasi-dynamic physical approximations. We use the RSQSim earthquake simulator to reproduce a 100 kyr synthetic catalog of earthquake ruptures based on a 3D fault model that contains the long-term slip rates, rakes and frictional properties of the main active sources of the Eastern Betic Fault System, a slow deforming area (< 1.5 mm/yr) at southeastern Spain with only one instrumental event greater than MW 5.0: the 2011 Lorca earthquake (MW 5.1). The resulting long-term earthquake statistics (more than 77.000 events) show that only about 10% of the simulated events have a magnitude greater than MW 5.0, but all faults in the system are capable of generating MW ≥ 6.0 earthquakes, supporting paleoseismic observations of surface ruptures and some historical events (I > VIII) that likely reached magnitudes greater than MW 6.0 (e.g., 1522 Alhama de Almeria and 1829 Torrevieja earthquakes). Complex ruptures involving several fault segments and spatial-temporal clustering of events are physically compatible in this system, according to our simulations. The largest MW > 6.5 events are as a result of complex ruptures between the major faults, with recurrence times of 1 kyr. The occurrence of larger earthquakes, even MW ≥ 7.0 in the Alhama de Murcia and Carboneras faults, cannot be ruled out, contrasting with the low magnitudes of the instrumental earthquake catalog. Knowing the characteristics and behavior of these large seismic ruptures, with no instrumental data available, is crucial for the estimation of the maximum ground motion that could be reached in this region. With this contribution, we intend to discuss how physics-based models could contribute to this task for deterministic and probabilistic seismic hazard assessments (DSHA and PSHA). Funded by Project DT-GEO: A Digital Twin for GEOphysical extremes, project ID 101058129.
The Kathmandu Valley as a science-policy laboratory: When science is insufficient to achieve clean air
Authors: Panday Arnico
Published: February 2023

Over the past decade the air pollution problem in the bowl-shaped Kathmandu Valley in Nepal – South Asia’s Mini-Mexico City – has become one of the most studied in the region.  Several international field campaigns resulted  50+ journal papers, while three separate networks now provide live air quality data to policymakers and the public.  They valley’s air pollution meteorology, emissions, ozone chemistry, aerosol chemical composition, health impacts, and the role of pollution transport have all been studied in detail.  At the same time, interdisciplinary task forces have laid out clear regulatory priorities and action plans for the Kathmandu Valley. Yet except for a decline in coarse dust (due to more roads getting paved), air quality has not improved in the Kathmandu Valley. Regulatory interventions have mostly been spontaneous, devoid of expert inputs, and short-lived.  There exists today sufficient scientific understanding to design a sophisticated regulatory framework that would respond to changing situations in real time to maintain the valley’s air quality.  But today that is just a dream.  As a front-row participant in the design of the field campaigns in the Kathmandu Valley, in policy making, and most recently in alternative politics, the author has unique insights into challenges that need to be overcome for there to be serious government action to clean up the Kathmandu Valley’s air.  At EGU he will share his insights into which scientific results did or did not end up being useful in shaping the public policy narrative, and why.  He will conclude his presentation by taking the lessons from the Kathmandu Valley from the past decade to provide general principals for other cities with air pollution problems but little data.
The Jordan Wind erosion And Dust Investigation (J-WADI)
Authors: Klose Martina , Pérez García-Pando Carlos ,   J-WADI Team
Published: February 2023

Knowledge about the particle-size distribution and mineralogical composition of mineral dust at emission are fundamental to advance our understanding and quantification of dust climate effects, yet comprehensive measurements are still largely lacking, especially of super-coarse and giant particles and particle composition. Here, we introduce the Jordan Wind erosion And Dust Investigation (J-WADI), an intensive field measurement campaign conducted in September 2022 north of Wadi Rum in Jordan. The aim of J-WADI is to improve our fundamental understanding of the emission of mineral dust, in particular its full-range size distribution (from fine to giant dust particles) and mineralogical composition. For this purpose, in-situ and ground-based remote sensing instrumentation was installed to measure aerosol properties, e.g. particle numbers and sizes up to about 100 μm, optical  properties, and aerosol distributions; collect soil and aerosol samples for laboratory analysis and experimentation; and to measure meteorological parameters including wind cross sections at high temporal and spatial resolutions and near-surface turbulence. In this contribution, we will present an overview of the J-WADI measurement setup and campaign conditions, together with preliminary results of observed dust events. In the future, J-WADI measurements will serve as a basis to investigate, e.g., (a) the mechanisms leading to the emission and continued suspension of super-coarse and giant dust particles and the possible variability of the emitted dust particle-size distribution; (b) the size-resolved mineralogy of dust at emission, its relationship with the parent soil, and spectroscopic measurement, and (c) dust-radiation and dust-cloud interactions.
“Zero Point” Background Screening of 137Cs and Pu isotopic composition for radiation environment in Eastern Lithuania
Authors: Puzas Andrius , Bernhardsson Christian , Pédehontaa-Hiaa Guillaume , Jönsson Mattias , Mattsson Sören , Tarasiuk Nikolaj , Konstantinova Marina , Gvozdaite Rasa , Druteikiene Ruta , Juzikiene Vida , Remeikis Vidmantas
Published: February 2023

Detection of environmental concentrations of radionuclides is the next step to complement data on abnormal events recorded by seismic, hydro-acoustic and infrasound station networks prior to asking for the approval of the on-site inspection. Radionuclides can travel hundreds of kilometres away from their source and under favourable meteorological conditions, be detectable in the air and when deposited on the ground. In order to determine and assess contributions to the anthropogenic radionuclides in the environment and to firmly distinguish it from previous global nuclear tests or emissions from nuclear facilities, it is essential to screen the background “zero point” of the anthropogenic radionuclides. This is especially important around existing sources e.g. nuclear power plants. In this work the radiochemical separation of radionuclides, alpha-, gamma- and mass-spectrometry measurement techniques were combined to determine concentrations and compositions of anthropogenic radionuclides in soil samples within 70 km radius around the Belarussian nuclear power plant in Astravec, on the territory of Lithuania. Gamma spectrometric measurements were performed with state-of-the-art alpha spectrometers and gamma spectra were acquired using an HPGe coaxial detector. Radionuclide isotopic ratios were measured by a sector field mass spectrometer combined with a high-sensitivity APEX sample introduction system. In this work 137Cs/239,240Pu, 238Pu/239,240Pu, 240Pu/239Pu isotopic “fingerprint” values revealed that previous nuclear weapon tests in the Northern hemisphere are prevailing in most of the sampling sites within a 70 km radius around Astravec NPP on the Lithuania territory.
Learning operational altimetry mapping from ocean models
Authors: Febvre Quentin , Fablet Ronan , Le Sommer Julien , Ubelmann Clément , Benaïchouche Simon
Published: February 2023

In oceanography, altimetry products are used to measure the height of the ocean surface, and ocean modeling is used to understand and predict the behavior of the ocean. There are two main types of gridded altimetry products: operational sea level products, such as DUACS, which are used for forecasting and reconstruction, and ocean model reanalyses, such as Glorys 12, which are used to forecast seasonal trends and assess physical characteristics. However, advances in ocean modeling do not always directly benefit operational forecast or reconstruction products.
In this study, we investigate the potential for deep learning methods, which have been successfully applied in simulated setups, to leverage ocean modeling efforts for improving operational altimetry products. Specifically, we ask under what conditions the knowledge learned from ocean simulations can be applied to real-world operational altimetry mapping. We consider the impact of simulation grid resolution, observation data reanalysis, and physical processes modeled on the performance of a deep learning model.
Our results show that the deep learning model outperforms current operational methods on a regional domain around the Gulfstream, with a 50km improvement in resolved scale. This improvement has the potential to enhance the accuracy of operational altimetry products, which are used for a range of important applications, such as climate monitoring and understanding mesoscale ocean dynamics.
Estimating the global lateral transfer of nitrogen through river network using a land surface model
Authors: Ma Minna , Zhang Haicheng , Regnier Pierre , Lauerwald Ronny , Ciais Philippe
Published: February 2023

Lateral nitrogen (N) transport from land to the ocean through rivers is an important component of global N cycling. In this study, we present the implementation of fluvial transport of nitrogen into ORCHIDEE-CNP (Organising Carbon and Hydrology in Dynamic Ecosystems-CNP), which explicitly simulates N biogeochemistry in terrestrial ecosystems coupled with carbon, water and energy transfers. This new model branch called ORCHIDEE-Nlateral, simulates the lateral transport of water, dissolved inorganic N (DIN), dissolved organic N (DON) and particulate organic N (PON) from land to the ocean through river networks, the decomposition of DON and PON, and the denitrification of DIN in transit. ORCHIDEE-Nlateral was parameterized and evaluated based on global observations of water discharge (Global Runoff and Dara Centre, GRDC) and N concentration in the global river network (Global Water Quality Archive, GRQA). The model reproduces well the observed riverine discharges of water and total nitrogen (TN), and N exports from the land to the ocean.  Globally, the TN flowing into rivers, denitrification of DIN and TN export to the ocean all increased from the year 1901 to 2015. The TN export to the ocean increased from 32 Tg N yr-1 to 37 Tg N yr-1 during 1901–2015, which is in good agreement with the corresponding global fluxes calculated from the well-established Global NEWS 2 model. In this study, we further re-assess the spatial and temporal distribution of global riverine N flows and stocks. Overall, our model approach represents a useful tool for simulating large-scale lateral N transfer and for predicting the future feedbacks between lateral N transfers and climate.
Effect of Indian Ocean Dipole on ocean meridional heat transport depends on ENSO
Authors: McMonigal Kay , Larson Sarah
Published: February 2023

Meridional heat transport within the Indian Ocean can drive climate and ecosystem impacts, by changing ocean temperature. Previous studies have linked variability in meridional heat transport to Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO). Recent studies have shown that some IOD events are caused by ENSO (termed “ENSO forced IOD”), while other events occur without ENSO (termed “internal IOD”). It is unclear whether these different kinds of IOD have different effects on the ocean. By comparing a climate model that includes ENSO to the same climate model but with ENSO dynamically removed, we show that internal IOD does not lead to variability in Indian Ocean meridional heat transport. However, ENSO forced IOD does lead to meridional heat transport variability. This is due to differing wind patterns associated with each kind of IOD event. These results suggest that the ecosystem and climate effects of IOD likely depend upon whether the IOD occurs with or without ENSO. 
Passive Microwave Retrieval of Soil Moisture Below Snowpack at L-Band Using SMAP Observations
Authors: Ardeshir Ebtehaj , Kumawat Divya
Published: February 2023

Soil and its water content can remain unfrozen below an insulative snow cover and modulate snowmelt infiltration and runoff. In this article, an emission model is proposed to account for L-band microwave emission of wet soils below a dry snowpack covered with an emerging moderately dense vegetation canopy. The model links the well-known Tau–Omega emission model with the snowpack dense media radiative transfer (DMRT) theory and a multilayer composite reflection model to account for the impacts of a snow layer on the upwelling soil and the downwelling vegetation emission, respectively. It is demonstrated that even though dry snow is a low-loss medium at the L-band, omission of its presence leads to underestimation of soil moisture (SM), especially when soil (snow) becomes wetter (denser). Constrained inversion of the proposed emission model, using brightness temperatures from the Soil Moisture Active and Passive (SMAP) satellite, shows that the retrievals of SM and vegetation optical depth (VOD) are achievable with unbiased root-mean-squared errors of 0.060 m3⋅m−3 and 0.124 [–], when compared with the in situ data from the International Soil Moisture Network (ISMN) and VOD-derived values from the normalized difference vegetation index (NDVI) obtained from the moderate resolution imaging spectroradiometer (MODIS) observations.
Pb and Sr Isotopic Compositions of Soils in Urbanized Industrial Settings, East Los Angeles, California, U.S.A: From Geogenic to Anthropogenic Sources
Authors: Ayuso Robert , Foley Nora , Johnston Jill , Indela Rani , Jackson John , Bickerstaff Damon
Published: February 2023

Preliminary lead and strontium isotopic compositions of soil profiles collected from highly urbanized and industrialized sites were measured to develop a survey of possible sources of lead. Potential lead and strontium sources range from geologic (e.g., bedrock and bedrock-derived soils) to anthropogenic (e.g., vehicular traffic and legacy of burning fossil fuels, heavy metal smelters, manufacturing of paint, plastics, lubricants, residential development, agricultural amendments, atmospheric deposition, etc.). Twenty-one soil profiles were sampled (6 samples/profile site to a depth of 60 cm). Lead concentrations and isotopic compositions (thermal ionization mass spectrometry and inductively coupled mass spectrometry) were measured for bulk soils, acid-leachates, and residues of bulk leaching. The soils include rock-forming silicates (e.g., feldspars, quartz, mafic minerals) and secondary minerals and amorphous materials (e.g., iron-oxyhydroxides, clays, organics). The lead isotopic compositions of acid-leachates of the soils represent lead adsorbed to mineral surfaces or held in soluble minerals (for example, iron- and manganese-hydroxides, and carbonate); soil residues likely reflect feldspar and other rock-forming minerals in bedrock-derived soils. The soils plot as a broad band in 206Pb/207Pb and 208Pb/207Pb space extending from radiogenic values (typical of rock-derived lead (bedrock and bedrock-derived soils) to lower 206Pb/207Pb and 208Pb/207Pb values that likely indicate anthropogenic/industrial types of lead (for example, heavy metal aerosols, leaded paint, agricultural amendments). Lead isotopic values of the Los Angeles soils form a broad band  intermediate between values of lead ores from the highly radiogenic U.S. Mississippi Valley type deposits and less radiogenic lead deposits of China.  Labile lead (leach fractions from soils) shows a moderate range in values of 206Pb/207Pb ~1.1671 to 1.1928, and 208Pb/207Pb ~2.4319 to 2.4498. Residues overlap the leach compositions and extend to more radiogenic values (rock-derived lead). The lowest values of 206Pb/207Pb (~1.1754) and 208Pb/207Pb (~2.4375) and highest lead contents (~4000 ppm) were measured in soils near where lead was smelted. Higher values of 206Pb/207Pb and 208Pb/207Pb and lower values of lead (~25 ppm) are found in other bulk soils and may represent lead derived from bedrock. The variations in lead isotope values in the soil profiles are consistent with contributions from distinct sources, which include both natural and anthropogenic lead.
Disaster risk factors and spatiotemporal trends in Africa
Authors: Eze Emmanuel , Siegmund Alexander
Published: February 2023

Africa’s disaster risk is fueled by vulnerability and lack of coping capacity factors, with specific components mostly missing in the literature. Having exceeded the midterm of the Sendai Framework for Disaster Risk Reduction (2015 to 2030), assessing the trend of disaster risk in Africa is necessary. This study answers two core questions: what are the disaster risk factors (and their interactions) in Africa? What trends and patterns have been observed in the last decade? Thus, this study determines the factors of disaster risk in Africa using random forest machine learning models and a Spatial Stratified Heterogeneity (SSH) technique using Geodetector software. Both analytical procedures gave rise to important factors (>10) of disaster risk in Africa. The interaction between these factors is also explored. Among the 22 variables included in the analyses, only one natural hazard (i.e., flood) is a significant factor, while current and projected violent conflicts are human-hazard factors of disaster risk in Africa. Additional results show the trend, pattern, and hotspots of African countries’ disaster risk in the last decade, based on the Index for Risk Management (INFORM) data. This study provides a broader understanding of disaster risk factors in Africa and their interactions, contributing to the foremost priority of the Sendai Framework for Disaster Risk Reduction. Furthermore, the trends, patterns and hotspots identified in this study show countries that should be prioritised for urgent actions.Keywords: Africa, disaster risk factors, disaster risk reduction, Random Forest, Sendai framework, Spatial Stratified Heterogeneity
Characterisation of the sensitivity to bias using a gain matrix formulation for the VeSUV/VenSpec-U instrument onboard ESA’s EnVision mission
Authors: Conan Lucile , Marcq Emmanuel , Lustrement Benjamin , Vandaele Ann Carine , Helbert Jörn
Published: February 2023

Selected in 2021 as the fifth class M mission of ESA’s “Cosmic Vision” programme, EnVision is one the three next exploration mission of Venus, alongside NASA’s VERITAS and DAVINCI. EnVision will bring a holistic approach, by studying the surface and subsurface, different layers of the atmosphere, past and present volcanic activity, as well as coupling processes. To that end, the payload will include a synthetic aperture radar for surface mapping (VenSAR, NASA), a subsurface radar sounder and a radioscience experiment to monitor gravimetric and atmospheric properties.Finally, the spectrometer suite VenSpec will investigate the surface and atmospheric compositions to analyse their relations with internal activity, using the thermal IR imager VenSpec-M and the high-resolution IR spectrometer VenSpec-H. The UV channel of the suite VenSpec-U, also called VeSUV, will focus on the atmosphere above the clouds, and aims more specifically at characterising the abundance and variability of sulphured gases such as SO and SO2, and the unidentified UV absorber. To do so, VeSUV will operate in pushbroom mode in the 190-380 nm range with an improved spectral resolution between 205 and 235 nm, and will observe the backscattered sunlight on the dayside of Venus at a spatial sampling ranging from 3 to 24 km.In order to characterise the instrument’s performances, the sensitivity to bias is analysed using a gain matrix formulation. A perturbation is locally introduced on a synthetic spectrum and a fitting algorithm involving the same radiative transfer model is used to retrieve the atmospheric parameters, for several values of perturbation. As they are small, the assumption of a linear relation between the perturbation and the resulting error on the estimated parameters is made, their ratio corresponding to the matrix element. This method allows a conversion between the measured signal and the atmospheric parameters independently from the bias spectrum (e.g. straylight, calibration error, contamination during mission), as it is computed separately for each wavelength.
A coupled GIS-MCDA approach to map the feasibility of Managed Aquifer Recharge
Authors: Chekirbane Anis , F. Panagiotou Constantinos , Dorsaf Aloui , Catalin Stefan
Published: February 2023

Managed aquifer recharge (MAR) is a water resource management technique that involves the intentional recharge and storage of water into groundwater systems. MAR is considered an innovative nature-based solution for increasing water availability, improving water quality, and reducing surface water runoff. However, the feasibility of implementing MAR projects depends on several factors, for example recharge water availability, water demand, and the intrinsic site characteristics (e.g., geology, hydrogeology) of the area.The current study proposes an adapted approach of MAR feasibility mapping through the integration of GIS and multi-criteria decision analysis (GIS-MCDA). The geospatial feasibility of MAR application is evaluated by considering the suitability maps of four thematic layers, namely intrinsic, water availability, non-physical and water demand.  The applicability of this approach is demonstrated in Enfidha plain (NE Tunisia), for which multiple types of spatial and temporal datasets have been collected.   The selection of the criteria is done based on literature studies and MAR experts’ opinions with respect to their relevance to MAR implementation, whereas the weights are determined using analytical hierarchy process (AHP). Hence, an intrinsic suitability map was established via the integration of ArcGIS software and MCDA in a web-based platform, called INOWAS (https://inowas.com/). The results suggest that more than 80% of the total plain area is considered intrinsically suitable for MAR implementation.  The potential MAR feasibility of the demonstration site is expected to be established by overlaying the suitability maps of the three thematic layers.In addition to standardizing the process of MAR feasibility, the derived maps constitute an asset in the process of planning and implementing effective MAR projects that help to ensure the long-term sustainability of water resources in the Sahel region of Tunisia.AcknowledgementThis work is funded by National Funding Agencies from Germany (Bundesministerium für Bildung und Forschung – BMBF), Cyprus (Research & Innovation Foundation – RIF), Portugal (Fundação para a Ciência e a Tecnologia – FCT), Spain (Ministerio de Ciencia e Innovación – MCI) and Tunisia (Ministère de l’Enseignement Supérieur et de la Recherche Scientifique – MESRS) under the Partnership for Research and Innovation in the Mediterranean Area (PRIMA). The PRIMA programme is supported under Horizon 2020 by the European Union’s Framework for Research and Innovation.