bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing tracer management for long and sustainable use of the Upper Jurassic geothermal reservoir in South Germany
Authors: Winter Theis , Zosseder Kai
Published: March 2024

The carbonate Upper Jurassic aquifer (UJA) in the South German Molasse Basin (SGMB) is the most important exploration horizon for geothermal energy supply in Bavaria. The UJA shows a complex hydrogeology caused by a heterogeneous geology with karstic features and deep fault zones.The great interest in the Upper Jurassic aquifer for geothermal energy supply led to an increasing construction of geothermal power plants in the greater Munich area. Today, there are 18 geothermal power plants in this area used for district heating and electricity generation.To guarantee a long and sustainable use of the geothermal resource, understanding the dynamics within the reservoir is important. Tracer tests are a key tool for investigating groundwater flow paths, detecting potential thermal breakthroughs, and minimizing negative interactions between geothermal power plants.In recent years, several tracer tests have been conducted, and the growing number of projects will lead to even more tracer testing in the coming years. Future tracer tests need to be carefully designed, as there is, up to now, only a limited number of traditional tracer substances available for use in a deep geothermal setting under high temperatures and pressures. Therefore, we developed tracer management for the UJA, including guidelines for different tracer tests, the suitability of different tracers for usage in a geothermal setting, and recommendations for individual locations.
Comparison of data-driven and physics-driven surface wave inversion
Authors: Chen Xinhua , Xia Jianghai , Hong Yu , Pang Jingyin
Published: March 2024

In near-surface investigations, the advent of massive seismic data has ushered in the application of deep learning (DL) techniques for surface wave inversion to attain the shear-wave velocity (Vs). While the efficiency of DL inversion surpasses that of classic physics-driven methods, its broader attributes remain underexplored. Our study delves into a comparative analysis of DL inversion versus physics-driven inversion, focusing on three key aspects: anti-noise ability, stability, and generalization.In numerical experiments, we employ the neighborhood algorithm (NA) (Wathelet, 2008) as a representative of physics-driven inversion, and a convolutional neural network (CNN) constructed for near-surface investigations (Chen et al., 2022) as a representative of data-driven inversion. In addition to comparing the two methods, we also explore the characteristics of joint inversion using Rayleigh-wave dispersion curves (DCs) and Love-wave DCs in the three above aspects. To quantitatively evaluate inversion results, we calculate the root mean square error and relative error of both DCs and Vs. The assessment of anti-noise performance involves applying NA and CNN to DCs with varying noise levels. To gauge stability, we introduce errors in compressional-wave velocity (Vp) and density, examining their effects on inversion precision. Lastly, to assess generalization, we use NA and CNN to invert DCs whose Vs exceeds the range of the training dataset by different percentages.Our findings reveal that DL inversion has a higher anti-noise ability compared with NA. Both methods demonstrate high stability, with errors in Vp and density exerting a slight impact on inversion results, aligning with surface wave inversion characteristics. Compared with physics-driven inversion, generalization is a unique feature of data-driven inversion. The experimental results indicate that the CNN can predict Vs models that are not included in the training dataset although this ability is somewhat limited. Furthermore, like physics-driven inversion, joint inversion enhances all three examined aspects for data-driven inversion. This analysis of characteristics can guide the selection of inversion methods for surface wave applications in near-surface investigations. References:Wathelet M., "An improved neighborhood algorithm: parameter conditions and dynamic scaling," Geophysical Research Letters, vol. 35, no. 9, pp. 2008, doi: 10.1029/2008GL033256.
Chen X., Xia J., Pang J., Zhou C., and Mi B., "Deep learning inversion of Rayleigh-wave dispersion curves with geological constraints for near-surface investigations," Geophysical Journal International, vol. 231, no. 1, pp. 1-14, 2022, doi: 10.1093/gji/ggac171.
What determines the simulated strength of the future North Atlantic carbon uptake?
Authors: Goris Nadine , Tjiputra Jerry , Johannsen Klaus , Olsen Are , Schwinger Jörg , Lauvset Siv , Jeansson Emil
Published: March 2024

The North Atlantic is one of the major sinks for anthropogenic carbon in the global ocean, yet future projections of its strength have presently high uncertainties. Here we analyze the mechanisms that determine the projected future North Atlantic carbon uptake of models and identify a list of variables that can be used to assess the associated model performance.
We focus on an ensemble of 11 Earth system models and their simulations of a future with high atmospheric CO2. Some of these models simulate that a slowdown in North Atlantic carbon uptake has already begun, while others simulate that this slowdown will only occur very late in the 21th century. Our results show that the highest model spread in the carbon uptake occurs in the high latitudes of the North Atlantic. The models with a high future anthropogenic carbon uptake reveal deep winter mixing and high primary production. Associated with this, we find that the simulated (i) high latitude winter pCO2-anomaly and (ii) upper-ocean northward volume transport between the surface and 500-m depth in the Gulf Stream area are good performance indicators for a model´s future carbon uptake in the North Atlantic.
The deep winter mixing and high primary production in models with high future North Atlantic carbon uptake enable an efficient carbon sequestration into the deep ocean, i.e. an efficient anthropogenic carbon drawdown in the Labrador and Irminger Seas, but furthermore an efficient southward transport of anthropogenic carbon out of the high latitudes via the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). Related to this, other well-suited performance indicators of the future carbon uptake of the North Atlantic are the simulated (iii) fraction of the carbon inventory that is stored below 1000-m depth and (iv) deep-ocean southward volume transport between 700 and 4700 m at 26∘N.
We use observation-based estimates of these four indicators to assess the model performance for the future North Atlantic carbon uptake. Our results falsify that the slowdown of the North Atlantic carbon uptake has already begun. We suggest that the strength of the AMOC is less suited as a performance indicator for the future North Atlantic carbon uptake than our newly identified indicators. Hence, the relation of maximum northward volume transport to the ocean carbon sink is not as robust as often assumed in modelling studies.
How exceptional was the September 2023 global heat? 
Authors: Seeber Svenja , Schumacher Dominik L. , Hauser Mathias , Seneviratne Sonia I.
Published: March 2024

In September 2023, the global mean surface temperature (GMST) anomaly reached a new maximum, exceeding the previous record by an unprecedented 0.5 °C. This is not only the highest monthly anomaly ever recorded, but also stands out compared to the more moderate anomalies seen during the record-breaking summer of 2023. It is likely that developing El Niño conditions are at least partly responsible for the anomalous heat. However, it remains unclear if such a sharp rise in global mean temperature is to be expected due to our warming climate and internal climate variability or if the September 2023 GMST was a rare event even for the current global warming level. In other words, could we soon witness even more intense monthly temperature anomalies? Moreover, are climate models able to adequately reproduce such extreme records? To address these questions, we analyze observations as well as CMIP6 model simulations and employ techniques from extreme event attribution. These statistical approaches typically focus on regional-scale weather and climate extremes. Here, we apply them to the September 2023 global heatwave to investigate the occurrence probability of this event, considering the influence of global warming as well as El Niño. 
Scenario-based Probabilistic Tsunami Risk Analysis for Coquimbo Bay
Authors: Jalayer Fatemeh , Ebrahimian Hossein , Catalan Patricio , Zamora Natalia , Soltani Saeed
Published: March 2024

Scenario-based tsunami risk assessment provides valuable insights into the socio-economic consequences of a specific scenario. Although it is focused on a specific scenario or a range of scenarios, this type of analysis can still encompass uncertainty characterisation. Hazard: Focusing on Coquimbo Bay, which was affected by the 2015 Ilapel tsunami, we demonstrate how the uncertainties are quantified and propagated from the tsunami source level all the way towards risk metrics such as the economic losses.  We have chosen a range of near-field tsunami scenarios with moment magnitude between 8.6
Mechanical stiffness and permeability of a reservoir-scale rough fracture during closure
Authors: Schmittbuhl Jean , Deng Qinglin , Cacace Mauro , Blöcher Guido
Published: March 2024

Natural or artificial fluid flow in deep fractured reservoirs, such as Enhanced Geothermal Systems (EGS), is primarily controlled by open fractures and faults, and is considered a key element for hydraulic performance. Flow along these fractures is strongly affected by channeling between fracture asperities and by deposits sealing the open fracture space due to mineral precipitation. Fracture asperities and fracture sealing also impact the mechanical behavior of fractures, especially their mechanical stiffness. Here, we study both the permeability and the stiffness of a rough fracture at the field scale during its closure.We base our approach on a well established self-affine geometrical model for fracture roughness. We develop a finite element model based on the MOOSE/GOLEM framework and conduct numerical flow experiments in a 256 × 256 × 256 m^3 granite reservoir hosting a single, partially sealed fracture under variable normal loading conditions. Navier-Stokes flow is solved in the embedded 3-dimensional rough aperture, and Darcy flow is solved in the surrounding poroelastic matrix. We study the evolution of the mechanical stiffness and fluid permeability of the fracture-rock system during fracture closure by considering the asperity yield and the depositing of fracture-filling material in the open space of the rough fracture. The evolution of the fault volume, fracture normal stiffness and permeability are monitored until fluid percolation thresholds are exceeded in two orthogonal directions of the imposed pressure gradient. Finally, we propose a physically based law for the stiffness and permeability evolution as a function of the fault volume. It is demonstrated that during closure, stiffness increases exponentially as the fault volume decreases. A strong anisotropy of the fracture permeability is also evidenced when reaching percolation thresholds.
QAnnAGNPS: a new plugin in QGIS to facilitate the use of AnnAGNPS
Authors: Barberena Iñigo , Campo-Bescós Miguel A , Casalí Javier
Published: March 2024

AnnAGNPS (ANNualized AGricultural NonPoint Source model) is a watershed-scale hydrologic model designed to analyze the impact of non-point pollutants in predominantly agricultural watersheds. It has capabilities that make it unique and indispensable on the world scene, such as an integrated simulation of all types of erosion and all major sources of non-point agricultural pollution. However, AnnAGNPS does not currently have a graphical user interface that allows the user to perform the simulation in a simple way. It is in this context that QAnnAGNPS has been created. QAnnAGNPS is a model developed in QGIS and written in Python 3 that fulfills two general functions. The first is to provide a simple to use graphical user interface to run AnnAGNPS. The second is to incorporate extra functionalities to the model, which are already included in similar hydrological models. The plugin has been used in the simulation of the Latxaga basin, a 207-hectare cereal basin located in Navarra (northern Spain). Its use has allowed to verify that QAnnAGNPS is able to perform the AnnAGNPS simulation and to visualize the results in a simpler way than the original one.
LiDAR assessment of sediment transport in a small, highly erosive alpine catchment
Authors: Boukhari Yassine , Le Bouteiller Caroline , Lucas Antoine , Jacquemoud Stéphane , Klotz Sébastien , Griffaton Mathilde
Published: March 2024

With rates locally exceeding one centimeter of denudation per year [1,2], i.e., more than 100 t/ha/year, the Durance basin in the French Alps is one of the world’s most heavily eroding areas [3]. A combination of favorable conditions explains this phenomenon, including a very steep topography, sparse vegetation and a particular susceptibility of the Jurassic black marls, also called Terres Noires, to seasonal climatic forcing [4]. The Draix-Bléone observatory uses hydro-sedimentary stations to instrument several of these small, non-anthropized catchments, where hydrological responses to seasonal storms are rapid and intense [5]. The work presented combines the use of LiDAR time series from airborne, UAV and ground measurements, with sediment flux chronicles recorded at the outlet of the Laval catchment, a small steep watershed (0.86 m2), to address questions of upstream/downstream transport modalities. An assessment of the potential of remote sensing methods for attributing the contributions of each critical zone compartment (channel, gullies, landslides, etc.) to the erosive dynamics of this basin and its connectivity is carried out.References :[1] N. Mathys, S. Brochot, M.  Meunier and D. Richard (2003). Erosion quantification in the small marly experimental catchments of Draix (Alpes de Haute Provence, France). Calibration of the ETC rainfall-runoff-erosion model. CATENA. 50(2–4):527–548. DOI : 10.1016/S0341-8162(02)00122-4.[2] A. Carriere, C. Le Bouteiller, G. E. Tucker, S. Klotz, and M. Naaim (2020). Impact of vegetation on erosion: Insights from the calibration and test of a landscape evolution model in alpine badland catchments. Earth Surf. Process. Landf., 45(5):1085–1099. DOI : 10.1002/esp.4741.[3] D. E. Walling (1998). Measuring sediment yield from river basins. in Soil Erosion Research Methods (R. Lal, Ed.). Soil and Water Conservation Society, Iowa, USA, pp 39–73.[4] L. Descroix and N. Mathys (2003). Processes, spatio-temporal factors and measurements of current erosion in the French Southern Alps: A review. Earth Surf. Process. Landf. 28( 9): 993–1011. DOI : 10.1002/esp.514.[5] Draix-Bleone Observatory. (2015). Observatoire hydrosédimentaire de montagne Draix-Bléone [Data set]. Irstea. DOI : 10.17180/obs.draix
Monitoring of La Palma 2021 volcanic eruption using Interferometric and Amplitude SAR data
Authors: Ezquerro Martín Pablo , Brú Cruz Guadalupe , Galindo Ines , Monserrat Oriol , López-Davalillo Juan Carlos , Sánchez Nieves , Montoya Isabel , Palamà Riccardo , Mateos Rosa María , Pérez-López Raul , González-Alonso Elena , Grandin Raphaël , Guardiola-Albert Carolina , López-Vinielles Juan , Fenández-Merodo José Antonio , Herrera Gerardo , Béjar-Pizarro Marta
Published: March 2024

Volcanic eruptions are a severe threat to approximately 800 million people living around 100 km from a volcano in 86 countries. For the eruptions affecting densely populated areas it is necessary to guarantee, during the emergency, the safety of the population, which requires a precise and reliable monitoring of the evolution of the volcano and the associated geological hazards.This work shows the application of monitoring products during an emergency. Under those circumstances some requirements like the quick availability of the satellite data, the availability of experts to generate the needed products or the accessibility of the results for the decision-making authorities are of crucial importance.During La Palma eruption in 2021, SAR data from 4 different satellites were used to generate three SAR-derived products to monitor the evolution of the morphology of the volcanic building, the extension of lava flows and ground deformation evolution in time. The availability of data from various satellites with different characteristics allows for their comparison, analyzing and identifying which is the optimal satellite and/or SAR dataset to generate each result.This work is part of the Spanish Grant SARAI, PID2020-116540RB-C21, funded by MCIN/AEI/ 10.13039/501100011033.
The relative importance of subglacial discharge and iceberg melt forcing in Greenlandic glacial fjord circulation
Authors: Johnstone Eleanor , Slater Donald , Cowton Tom , Fraser Neil , Inall Mark , Mas e Braga Martim
Published: March 2024

Glacial fjords form a crucial coupling between the Greenland ice sheet and the surrounding ocean, but observational data is scarce and their complex multi-scale physics can be difficult to model. Thus, glacial fjord processes are often excluded from large-scale ice sheet models that project  sea level contribution and ocean models that are forced by ice sheet freshwater. A key driver of fjord dynamics is the input of ice sheet freshwater, primarily from subglacial discharge rising in a buoyant plume and from iceberg melt. These freshwater sources set up a density gradient between the fjord and shelf, driving fjord circulation and exporting freshwater to the ocean. Observational evidence from a few fjords suggests that fjords can store this freshwater, leading to an export to the shelf that is modified in properties and lagged in time compared to the input of the freshwater to the fjord. Yet little is known about how this freshwater modification varies across Greenland’s diverse fjords, and the relative importance of the sources of freshwater in this process has not been quantified.  Here, we use a two-layer box model to simulate fjord dynamics in a simple yet realistic way. We isolate the circulation driven by freshwater input from each of subglacial discharge and iceberg melting to assess the relative impact of each process on (i) strength of circulation and (ii) modification and export of freshwater. The model suggests that fjord geometry and the strength of the fjord-shelf exchange are the key controllers of the lag time for freshwater export, with strong fjord-shelf exchange and smaller fjords promoting nearly instant freshwater export, and weak fjord-shelf exchange and large fjords giving long lags in freshwater export. The wider aims of the project are to quantify freshwater export and heat import at glacial fjords on a Greenland-wide scale.
CFD, a radiative model, and a plant model to capture the interactions between solar panels, the atmosphere, the soil, and the plants in agrivoltaic configurations.
Authors: Vernier Joseph , Edouard Sylvain , Amiot Baptiste , Van Iseghem Mike , Ferrand Martin , Combes Didier , Schuchardt Guillaume , Massin Patrick
Published: March 2024

Currently, our understanding of the impact of agrivoltaic systems on the crops is limited. The presence of panels modifies the micro-climate and therefore the radiative, thermal, and aeraulic exchanges between the crop and its surrounding (S. Edouard, 2022). These modifications can lead to a loss of agricultural production, but also to a crop protection against meteorological events. Crop models, such as DSSAT, are not suitable to study the impact of solar panels on crop growth as spatial and temporal averages in the models hide spatial heterogeneities caused by the panels, and the sub-daily phenomena are not simulated. Computational fluid dynamic (CFD) allows high-fidelity simulations of multi-physics problems on different time and length scales (such as thermal hydraulics in power plants, or the drag of a wind farm). First CFD simulations applied to agrivoltaics have been carried out by (S. Zainaly, 2023), and by (H. J. Wiliams, 2023). Through Joseph Vernier’s PhD thesis, EDF R&D has initiated CFD modeling applied to agrivoltaics.
 
The CFD solver code_saturne simulates the flow over the panels, as well as the radiation, the temperature, and the humidity fields. Moreover, a 2 layers force-restore soil model computes the energy and the water exchanges between the soil and the atmosphere. The effect of the micro-climate on the photosynthesis and the plant stomatal resistance must be considered to accurately predict the plant growth. That is why, the soil-plant-atmosphere continuum model (A. Tuzet, 2003) has been implemented in code_saturne and a simplified study case composed of four solar panels has been built. First simulations of the modifications of the micro-climate by the solar panels and how it impacts the crops are very promising. Indeed, spatial heterogeneities are well simulated for the radiation, and the soil temperature (Figure 1-4), as well as for the wind speed (Figure 5, 6), the plant temperature, the photosynthesis, and the evapotranspiration. Simulations of the impact of shading on the soil water balance reveals that the plant’s energy balance is locally modified in a complex fashion that depends on the agrivoltaic power plant geometry. Water stress is considered, and it interferes with the plant's ability to photosynthesize and to transpire. Thanks to the coupling of code_saturne and the soil-plant-atmosphere continuum model, the plant state is simulated along the day for different weather conditions and agrivoltaic configurations. This is a first step towards a deeper understanding of the physical interactions within a photovoltaic system.
Springtime observations of black carbon aerosols in and outside of low-level Arctic clouds
Authors: Nilsson Lovisa , Thomasson August , Zieger Paul , Asplund Julia , Roldin Pontus , Mattson Fredrik , Ahlberg Erik , Swietlicki Erik
Published: March 2024

Few expeditions have ventured into the Arctic to observe the processes that take place in the transition from winter to summer. Particularly, direct observations of aerosol-cloud interactions are scarce, and comprise a large source of uncertainty in radiative forcing estimations in the Arctic.Light absorbing aerosol particles, such as black carbon (BC) from incomplete combustion, exert a positive forcing upon direct absorption of sunlight, and affect clouds by serving as cloud condensation nuclei (CCN). During the icebreaker expedition ARTofMELT in spring 2023, we measured BC with a multi-angle absorption photometer (MAAP) and a single particle soot photometer (SP2) for five weeks. The two instruments differ by principle and can be used to inform on complementary aspects of the light absorbing aerosol. For example, the MAAP provides the total mass concentrations of so-called equivalent BC (eBC), whereas the single particle instrument SP2 determines the mass of individual refractory BC (rBC) aggregates. Most of the time, the MAAP and SP2 sampled the total BC concentration on the same inlet (whole-air). However, during cloud-events, the SP2 measured downstream of a counterflow virtual impactor (CVI) inlet that samples just cloud droplets or ice crystals without the interstitial or non-activated aerosol.Our first results indicate overall low out-of-cloud BC mass concentrations for both instruments (median and interquartile range, IQR: 4.4 (1.6-8.5) ngm-3 for the MAAP and 2.5 (1.2-4.7) ngm-3 for the SP2). The variation in mass concentration was small, although the tendency of a gradual decrease was observed towards the onset of the melt.The SP2 instrument enables studies of the BC mass size distribution. For example, during a cloud event we observed that the geometric mean diameter (GMD, mass equivalent diameter) shifted from smaller (171 nm, whole-air inlet) to larger sizes (175-192 nm), as the SP2 switched to sampling the cloud-residual BC (CVI inlet). Further investigation is needed to examine the underlying causes for this observation (e.g. variation in airmass origin). The total aerosol concentration is influenced by local natural sources and production from gaseous precursors, as opposed to the BC concentration which is mainly affected by anthropogenic activities. BC source footprints from the Lagrangian dispersion model FLEXPART, indicate little influence from industrialized regions during the whole campaign. This may explain the comparably low median concentration of rBC-particles (1.1 cm-3, IQR: 0.5-2.1) to the total aerosol number concentration (in the range ~20-150 cm-3).
First Synthetic Isotopic Methane Gas Reference Materials for Optical Isotope Ratio Spectroscopy
Authors: Hopkinson Emily , Safi Emmal , Rennick Chris , Hillier Aimee , Mussell-Webber Eric , Moossen Heiko , Wilson Freya , Hill-Pearce Ruth , Worton David , Brewer Paul , Arnold Tim
Published: March 2024

Isotope ratio is a powerful tool for discriminating between sources and sinks of greenhouse gases, enabling their source apportionment. We have produced the first high volume and high-pressure methane (CH4) gas reference materials with a certified δ13C-CH4 and δ2H-CH4 in a synthetic air matrix. This matrix contained ambient amount fractions of the major air components and key greenhouse gases CO2 and N2O.The SI traceable methane in air reference materials were gravimetrically produced in 10 L cylinders at a pressure of 100 bar to fulfil the high-volume calibration requirements of optical isotope ratio spectroscopy (OIRS) techniques. The methane sources were chosen to span the observed atmospheric δ13C-CH4 and will be used to monitor the isotope ratio of atmospheric methane at sites across Europe.The δ13C-CH4 and δ2H-CH4 of pure methane sources and diluted methane references were measured via isotope ratio mass spectrometry (IRMS). The diluted methane reference materials were used to characterise an OIRS (Aerodyne Research Inc.) analyser fitted with an in-house built pre-concentrator. Further methane sources were characterised for δ13C-CH4 and δ2H-CH4 after dilution on the calibrated Aerodyne to create a suite of reference materials with δ13C-CH4 values spanning -51.94 to -39.19 ‰ and -202.56 to – 182.04 ‰ for δ2H-CH4.Uncertainty budgets for the diluted reference materials will be presented with gravimetric amount fraction uncertainties aiming towards the World Metrological Organization Global Atmosphere Watch (WMO-GAW) compatibility goal of 2 nmol mol-1 across the amount fraction range of 1.75-2.10 µmol mol-1. Reference materials were produced at a range of amount fractions (1.7 to 569 µmol mol-1) required to calibrate different OIRS techniques. Commonly interfering matrix components Ar, O2, CO2 and N2O were added at ambient amount fractions (420 µmol mol-1 and 335 nmol mol-1 for CO­2 and N2O respectively). Approximately 30 reference materials, each containing around 1000 litres of gas were distributed to seven partners in the EMPIR Metrology for European emissions verification on methane isotopes (isoMET) project. Measurements using these reference materials will enable comparability of isotopic methane data collected as part of national and international monitoring networks.
Inversion of the global NH3 emissions (2019-2022) based on IASI NH3 observations and the LMDZ-INCA chemistry-transport model 
Authors: Kumar Pramod , Ciais Philippe , Hauglustaine Didier , Broquet Gregoire , Clarisse Lieven , Van Damme Martin , Coheur Pierre
Published: March 2024

Atmospheric ammonia (NH3) has significant environmental impacts, contributing to biodiversity loss and air quality deterioration, with potential negative effects on ecosystems and human health. The global and regional NH3 emissions have been on continuous rise in the recent years, due to the extensive use of fertilizers in agricultural activities and to livestock production. However, the current bottom-up NH3 emission inventories exhibit large uncertainties at all the spatiotemporal scales. Top-down estimates of the global and regional NH3 emissions from the atmospheric inversion approach based on satellite observations with global coverage can provide valuable insights on the spatiotemporal variability of ammonia emissions. In this study, we provide top-down atmospheric inversion estimates of the worldwide anthropogenic NH3 emissions using the new version 4 of the IASI ANNI NH3 observations for a period of four years from 2019 to 2022 at 1.27°×2.5° (latitude × longitude) horizontal resolution and at daily (as a 10-day running average) temporal scale. We use a global chemistry transport model LMDZ-INCA for the NH3 concentrations simulations and a finite difference mass balance approach for the inversions of the NH3 emissions. We take advantage of the vertical averaging kernels provided in version 4 of the IASI NH3 data product by applying them consistently to the LMDZ-INCA NH3 simulations when evaluating these simulations. We perform the global inversions to estimate the anthropogenic NH3 emissions, using the IASI NH3 total columns observations and LMDZ-INCA NH3 total columns convolved with the vertical averaging kernel. The global annual anthropogenic NH3 emissions averaged over the four years period (2019-2022) are estimated as ~90 (88-92) Tg yr-1. These global estimates are ~70% higher than the prior CEDS inventory NH3 emissions used in the inversions and significantly higher (more than by a factor for two) when compared to two other global bottom-up inventories, CAMS and CAMEO. The regional NH3 emissions estimates derived from our global inversion are also assessed through comparisons with other inventories and recent top-down estimates based on the satellites NH3 observations. Our estimates of the NH3 emissions at both the global and regional scales are mostly consistent with other top-down inversion estimates. 
Effect of climate change on lightning induced forest fires in Austria
Authors: Laimighofer Johannes , Andrade Mariana Silva , Echtler Pia , Fuchs Sven , Müller Mortimer , Papathoma-Köhle Maria , Vacik Harald , Formayer Herbert
Published: March 2024

Increasing temperatures, due to climate change lead to more evapotranspiration which increases the possibility of severe drought periods. These trends enhance the risk of wildfire hazards even in humid regions like the Alps. Further, possible changes in the occurrence of thunderstorms can modify the ignition danger of lightning induced wildfires. This study aims to investigate the effect of climate change on the probability of wildfires ignited by lightnings including possible shifts in lightning probability for Austria.The full analysis is performed on a 1x1 km grid over Austria. Fire ignition danger and drought periods are approached by computing the Fine Fuel Moisture Code (FFMC). Noon temperature and windspeed for the FFMC are estimated by a spatio-temporal GAM (generalized additive model) with a geographic varying cyclic B-spline. The occurrence of lightnings is approached by the Showalter Index, which is validated with data from the Austrian Lightning Detection and Information System (ALDIS) for the period 2011 to 2020. For the historical weather conditions the Spartacus dataset is used for the period 1981-2022. Regarding the future development, five different climate projections are compared.The historical period showed on average no trend for days with high FFMC values (> 91) for Austria, but already 13% of the study area have a significant positive trend (tested by Mann-Kendall trend test). The trend is even more evident for the climate projections, which show a significant increase in days with FFMC values > 91 for 99% of the study area, with a sharp increase starting about 2050. Possible alterations in thunderstorm activity will strengthen the danger of forest fire ignitions of wildfires in Austria and are posing an increasing threat for forest management and society. 
Executable Book for the IPCC AR6 ATLAS products
Authors: Cofiño Antonio S. , Dominguez Roman David
Published: March 2024

Internationally-coordinated climate model intercomparison projects (MIPs) explore the uncertainties inherent to climate change science. The Multi-MIP Climate Change ATLAS repository [1] is the backbone of the Sixth IPCC Assessment Report (AR6) Atlas Chapter, which provides a region-by-region assessment of climate change including also the innovative Interactive Atlas [2]. The Interactive Atlas complements the report by providing flexible spatial and temporal analyses of regional climate change, based on different MIPs.The IPCC AR6 promotes best practises in traceability and reproducibility of the results shown in the report, including the adoption of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles for scientific data. In particular, reproducibility and reusability are central in order to ensure the transparency of the final products. The ATLAS products are generated using free software community tools, based on the climate4R framework [3], for data post-processing (data access, regridding, aggregation, bias adjustment, etc.), evaluation and quality control (when applicable). All the ATLAS code is made publicly available as notebooks and scripts [1].The Executable Book Project (EBP) [4] is an international collaboration between several universities and open source projects, to build tools that facilitate computational narratives (books, lectures, articles, etc …) using open source tools allowing users from scientific and academic communities to be able to: merge rich text content, output from live code, references, cross-references, equations, images, etc; execute content and cache results; combine into a document model, cached outputs and content files; build interactive (i.e. HTML) and publication-quality (PDF) outputs; and control everything from a simple interface. In this contribution, a demonstration of a computational book has been created using the JupyterBook ecosystem, binding the code scripts and the notebooks from the Multi-Model Intercomparison Project (Multi-MIP) Climate Change Atlas repository to improve its reproducibility and reusability. Acknowledgement: This work is partly supported by: project CORDyS (PID2020-116595RB-I00) funded by MCIN/AEI/10.13039/501100011033; Ministry for the Ecological Transition and the Demographic Challenge (MITECO) and the European Commission NextGenerationEU (Regulation EU 2020/2094), through CSIC's Interdisciplinary Thematic Platform Clima (PTI-Clima); and, the ENES-RI and IS-ENES3 project which is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824084 [1] https://github.com/SantanderMetGroup/ATLAS[2] http://interactive-atlas.ipcc.ch[3] https://github.com/SantanderMetGroup/climate4R[4] https://executablebooks.org
Studies on radon time series in various underground environments: Case of abandoned Kővágószőlős uranium mine
Authors: Szabolcs Tóth , Ákos Horváth , László Sajó-Bohus
Published: March 2024

Field uranium research began in Hungary in 1947 under the guidance of Hungarian specialists. After the research period, mining plants were opened one after the other, and an ore processing plant was also established. The ore grade found in the Mecsek Mountains was less favorable than average, 1 ton of ore contained 1.2 kg of uranium metal. The characteristic of the uranium ore found in the permian sandstones is that it occurs in several layers and levels, not continuously, but in lenticular spots with varied development. This geological occurence significantly increased the costs. By 1989, Hungarian uranium ore mining had become uneconomical, and a government decision was made to close it down, dating back to 1997. The recultivation process began in 1998. Currently, environmental damage is being eliminated under the title of long-term monitoring. Due to the proximity of inhabited areas, NORM anomalies, and the presence of radon gas, radiation protection played a particularly important role during and after remediation.The radon monitoring of the abandoned mine cavity system was carried out with active radon monitors placed in different boreholes, closed shafts and adits. In the last two years, a radon soil gas monitoring station has also been operated on a waste rock pile site covered with 1 m of loess cover to check the radon retention capacity of the soil.For radon detection alpha-sensitive photodiode (sensitive area: 1 cm2) or PIPS detector (sensitive area: 3 cm2) are used. The Dataqua monitoring system gives one impulse per hour for 140 and 56 Bq/m3222Rn concentration, respectively, for the photodiode and PIPS detector. The multi-channel devices beside the radon detector can include other additional sensors for temperature, pressure, humidity, water level, salinity, etc. measurements to study the relation between the variation of radon concentration and other environmental parameters. The radon concentration together with other environmental parameters are continuously recorded with one measurement per hour sampling frequency for several years.In closed, underground places extremely high radon concentration (a couple of tens up to hundred kBq/m3, may occur in the absence of ventilation, even in rocks of average radionuclide content. According to our measurements both the daily and the yearly variation is well recognizable, which originate from the variation of the meteorological and lunisolar parameters. In the case of a few time series, we revealed a strong correlation between the outside temperature and the resulting radon concentrations.  We found the atmospheric pressure also affects radon levels, but extent and only on a smaller scale than temperature. Comprehensive statistics and Fourier analysis were also carried out in order to examine the dominant frequencies, and we also examined the change of the one day long components as a function of time.
Characterization of Sulfamethoxazole Direct Photodegradation through Multi-Element Compound-Specific Isotope Analysis
Authors: liu xiao , Köpke Jimmy , akay caglar , Kümmel Steffen , Richnow Hans Hermann , Imfeld Gwenaël
Published: March 2024

The direct photodegradation of sulfamethoxazole (SMX) represents a significant dissipation process in wetlands. However, distinguishing photodegradation from concurrent processes such as microbial and plant degradation in these environments presents a challenge. Therefore, our objective was to employ novel isotope concepts to characterize and differenciate the specific mechanisms involved in photodegradation processes. The GC-IRMS method developed for SMX includes carbon, hydrogen, and nitrogen isotope analysis, while the GC-MC-ICP-MS method specifically caters to sulfur isotope analysis. SMX exhibits varying protonation states at different pH levels, significantly affecting its degradation kinetics. We conducted direct photodegradation of SMX in simulated sunlight (>280nm) at pH 3 and pH 7. Degradation was faster at pH 3 than at pH 7. We observed normal carbon and sulfur isotope fractionation, yielding carbon isotope fractionation values (εC) of -1.9 ± 0.2 at pH 7 and -2.7 ± 0.4 at pH 3. The sulfur isotope fractionations (ε34S) were -3.7 ± 0.5 at pH 7 and -6.3 ± 0.5 at pH 3, while ε33S values were -6.4 ± 1.2 at pH 7 and -7.5 ± 1.1 at pH 3. In contrast, an inverse nitrogen isotope fractionation was observed, with εN = 3.0 ± 0.2 at pH 7 and 3.6 ± 0.1 at pH 3. These results support the idea of an involvement of carbon, nitrogen, and sulfur in the bond cleavage during the rate-limiting step. However, insignificant changes in the hydrogen isotopic compositions of SMX during degradation suggest that either hydrogen was not significantly involved in the bond cleavage or the transformation realted to the hydrogen bond cleavage played a minor role in the overall degradation process. Overall, the isotope data highlighted distinct transformation pathways during direct photodegradation at different pH levels. At pH 7, the dominant transformation products were sulfonilic acid, 3-amino-5-methylisoxazole (3A5MI) from N-S bond cleavage, 5-methylisoxazol-3-yl)sulfamate from C-S bond cleavage, and sulfanilamide from C-N bond cleavage, which aligned with the observed isotope fractionation data. Conversely, at pH 3, different dominant transformation products, including sulfonilic acid, 3A5MI, N4-hydroxylation of sulfanilamide and SMX isomerization, suggest that transformation pathways differed from those observed at pH 7. Altogether, the specific isotope fractionation signatures derived from multi-element CSIA for direct photodegradation of SMX represent a unique reference enabling future comparisons with other degradation pathways.
Dual-lobe reconnection, horse-collar auroras, and cusp-aligned arcs
Authors: Milan Steve , Mooney Michaela , Bower Gemma , Paxton Larry , Vines Sarah , Hairston Marc
Published: March 2024

We propose a mechanism for the formation of the horse-collar auroral configuration during periods of strongly northwards interplanetary magnetic field, invoking the action of dual-lobe reconnection (DLR).  Auroral observations are provided by the Imager for Magnetopause-to-Auroras Global Exploration (IMAGE) satellite and spacecraft of the Defense Meteorological Satellite Program (DMSP).  We also use ionospheric flow measurements from DMSP and polar maps of field-aligned currents (FACs) derived from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE).  Sunward convection is observed within the dark polar cap, with antisunwards flows within the horse-collar auroral region, together with the NBZ FAC distribution expected to be associated with DLR.  We suggest that newly-closed flux is transported antisunwards and to dawn and dusk within the reverse lobe cell convection pattern associated with DLR, causing the polar cap to acquire a teardrop shape and weak auroras to form at high latitudes.  If the process continues, the cusp-aligned arcs auroral configuration ensues.  Horse-collar auroras and cusp-aligned arcs are a common feature of the quiet magnetosphere, and this model provides a first understanding of their formation, resolving several outstanding questions regarding the nature of DLR and the magnetospheric structure and dynamics during northwards IMF.  The model can also provide insights into the trapping of solar wind plasma by the magnetosphere and the formation of a low-latitude boundary layer and cold, dense plasma sheet.
Influence of data assimilation on tropical waves
Authors: Ruckstuhl Yvonne , Janjic Tijana , Jung Hyunju , Knippertz Peter , Redl Robert
Published: March 2024

Precipitation forecasts in the tropics are poor due to large model and initial condition errors, leaving ample room for improvement. In particular, it has been hypothesized that the coupling of tropical waves and convection offers a source of predictability, suggesting that capturing these waves accurately in the model and in initial conditions could lead to improved precipitation forecasts. In this work, we investigate whether standard data assimilation (DA) algorithms like the Ensemble Kalman Filter (EnKF) are fundamentally capable of recovering tropical waves and thereby provide initial conditions that lead to skillful precipitation forecasts. To capture the essence of tropical dynamics without contamination of land-sea contrasts, sea-surface temperature gradients and influences from the extra-tropics, we use a tropical aqua channel configuration at 13km grid-spacing with the ICON numerical weather prediction model. Further, to isolate the role of the initial conditions provided by DA, we assume a perfect model. In our setup, Kelvin waves dominate over other wave types and primarily modulate precipitation.  In addition, there is evidence of a Madden-Julian-Oscillation (MJO)-like feature that appears coupled to large-scale convective activity. We show that when sufficient wind observations are assimilated, the DA can reduce the errors in the representation of the Kelvin waves sufficiently to provide accurate precipitation forecasts up to several weeks. Surprisingly, even the MJO-like rainfall event, which starts after a forecast lead time of 10 days, is captured by the forecast ensemble. Further, we find that accurate initial conditions for humidity are important to slow down error growth for all model variables. Like emphasized by several other studies, we conclude that wind observations are by far the most important input to achieve skillful tropical forecasts. A secondary challenge is to improve initial conditions of humidity by developing DA algorithms to account for non-Gaussian error statistics. Investigating the role of model error in DA and the resulting forecasts is left for future work. 
 Identification of primary productivity hotspots and their association with oceanographic phenomena in the coastal region off Central Norway
Authors: Ellingsen Ingrid Helene , Broch Ole Jacob , Moreira Fragoso Glaucia
Published: March 2024

The coastal waters of Central Norway showcase a great biodiversity. The Froan archipelago and the coral reefs of the Sula rise are highly productive, with several species of fish, clams and crab. Results from the ocean model system SINMOD show a high primary production in the area as a result of internal waves at the shelf break in combination with strong tidal mixing at the bank area of the Froan archipelago. Oceanographic conditions strongly impact on the phytoplankton community structure and succession in this region (Fragoso et al., 2019, Fragoso et al. 2021). Spring bloom dynamics is further sensitive to rapid changes in weather in the region (Fragoso et al, in revision).In this study, we use the coupled biophysical SINMOD model to explore spatiotemporal variations in primary production. We aim to correlate these variations with internal waves, tidal mixing, and eddies across different regions of the complex shelf area. The observations from previous studies will be used to assess the model prediction skill. We will further investigate the fate of carbon in the system and use the model results to locate potential hot spots of biodiversity by investigating vertical transport of carbon as well as recycling of carbon in the water column. This work is part of an ongoing interdisciplinary project AMBIOS that aims to develop a fully autonomous system for the discovery of, and navigation to, marine microbial biodiversity hotspots.
Diverse flood characteristics over southern High Mountain Asia under different synoptic patterns
Authors: Zhu Yanxin
Published: March 2024

High Mountain Asia (HMA) supplies abundant natural and human water demands in Asia, nourishing about 30% of global population, which is of vital importance to sustainable water resources management. However, the space-time pattern of flood characteristics and its related synoptic conditions in this region remains unclear. This study illuminates the discrepancy of flood characteristics in two stages of warm season over the southern HMA, particularly the spatial propagation, scale and frequency of floods. In the first stage, more local-scale floods occur and propagate from the downstream to the upstream, while in the second stage, there would be more widespread and high-magnitude floods in this region. The tributaries are characterized by local-scale floods, but with a higher frequency in the first stage than the second stage. Diverse synoptic patterns of Indian Low Pressure (ILP) and Western Pacific Subtropical High (WPSH) are responsible for the individual characteristics of floods. The WPSH is favorable for facilitating a massive amount of moisture from the Pacific and Indian Ocean to southern HMA, and thus tends to induce the intensive and widespread floods in the second stage. A shift of earlier and later flood peak dates in the historical period is shown in the first and second stage, respectively. Effective measures need to be implemented to cope with the spatial and temporal variability in flood characteristics by integrating the tradeoffs between freshwater management and flood risks mitigation.