bluuebunny/crossref_metadata_2025 huggingface dataset:
On the plausibility of methane detections on Mars
Authors: Viscardy Sébastien , Robert Séverine , Erwin Justin T. , Thomas Ian R. , Daerden Frank , Trompet Loïc , Willame Yannick , Vandaele Ann Carine
Published: February 2023

As a potential biomarker, Martian methane has attracted attention through several reports of its detection over the last 20 years. However, the very existence of this gas has been continuously questioned, in particular because the observed lifetime should be several orders of magnitude shorter than the 300 years predicted by photochemical models. Although several fast removal processes have been hypothesized to explain the observations, none of them has met a large consensus.
It is in this context that the ESA-Roscomos ExoMars Trace Gas Orbiter (TGO) mission started its science operations in April 2018. ACS and NOMAD, two instruments onboard the TGO, have been collecting hundreds of highly sensitive measurements in solar occultation. No methane has been detected so far and an upper limit of 0.02 ppbv has been derived. The implications of this result on the methane problem on Mars will be addressed in this work.
This upper limit is a strong constraint on the background level and, in turn, on the potential emission scenarios making the reported methane detections consistent with the TGO results. While several model studies aimed at identifying them, we will here adopt a probabilistic approach to the problem in order to question the plausibility of those detections and estimate the lifetime required to make them plausible from a probabilistic standpoint.
Greenhouse gas emissions from bog peatlands subjected to (potential) mitigation meausures
Authors: Tiemeyer Bärbel , Brümmer Christian , Dettmann Ullrich , Düvel Dominik , Heller Sebastian , Oestmann Jan , Offermanns Liv , Piayda Arndt , Welpelo Carla
Published: February 2023

Drained organic soils are large sources of anthropogenic greenhouse gases (GHG) in many European and Asian countries. In Germany, they account for more than 7% of the national GHG emissions. Carbon dioxide (CO2) forms the vast majority of emissions from these soils and is thus the main target for mitigation measures. Bog peatlands are mainly found in North-Western Germany and frequently used for high-intensity grassland use. Further, former peat extraction areas are restored for nature protection. While restoration has decades of tradition, paludiculture and active water management in agriculture are comparatively new.Here, we will compile data on GHG exchange of bog peatlands and highlight recent results on water management by ditch blocking and subsurface irrigation, on Sphagnum paludiculture and on restored bog peatlands. Groundwater levels are usually considered as the major control for both CO2 and methane (CH4) emissions. The effects of water management on CO2 emissions are strongly depending on the site. Surprisingly, raising the groundwater level by subsurface irrigation in a grassland under bog peat to levels considered as acceptable even in restoration projects did not only fail to reduce CO2 emissions, but raised them compared to deeply drained control parcel. These results might be explained by an interaction of increased soil moisture in the topsoil and improved nutrient retention during phases of high soil temperatures and, at the same time, by limitations of microbial activity due to low soil moisture at the control parcels. However, at a second grassland site with subsurface irrigation, this did not occur, but a combination with grassland renewal caused extremely high nitrous oxide emissions. In contrast, both re-wetting for restoration purposes and Sphagnum farming reliably reduce GHG emission or may even lead to a carbon sink. Here, the effects of the groundwater level on CO2 and, even more, on CH4 emissions in a Sphagnum farming experiment were partially overridden by vegetation development dynamics.
Carbonate Compensation Depth in Exoplanet Oceans and Ocean pH
Authors: Hakim Kaustubh , Tian Meng , Bower Dan J. , Heng Kevin
Published: February 2023

The carbonate-silicate cycle is thought to play a key role in maintaining temperate climates on Earth via continental silicate weathering and seafloor carbonate precipitation. Present-day carbonate precipitation on Earth’s seafloor is mainly attributed to calcium carbonates. However, observations of refractory element ratios in stellar photospheres and planet formation models suggest a large diversity in exoplanet bulk composition and thereby the near-surface composition. In this work, we compute exoplanet ocean pH and carbonate compensation depth (CCD). We find that ocean pH exhibits a limited range of values as a function of ocean temperature and partial pressure of CO2, where the limits are given by the absence and presence of carbonates. The CCD increases with ocean temperature and partial pressure of CO2. If the CCD is above the seafloor, the carbonate-silicate cycle ceases to operate and therefore high ocean temperature and partial pressure of CO2 favor the carbonate-silicate cycle. With the help of pure carbonate systems of key divalent elements, we show that magnesium, calcium and iron carbonates produce an increasingly wider parameter space of deep CCDs, suggesting that chemical diversity promotes the carbonate-silicate cycle. This work motivates the inclusion of more chemically diverse targets than Earth twins in the search for life in exoplanets.
Quantification of Secondary Sulfate emissions in Europe and Central Asia
Authors: Vratolis Stergios , Eleftheriadis Konstantinos
Published: February 2023

The scope of this work is to quantify the emission rate of Secondary Sulfate across a wide region in the Northern hemisphere, mainly in Europe and Western Asia. The data employed are deducted by Positive Matrix Factorization (PMF) on a PM2.5 chemical composition dataset from 16 European and Asian cities for the period 2014 to 2016. The spatial resolution of the method corresponds to the geographic grid cell size of the Lagrangian particle dispersion model (FLEXPART) which was utilized for the air mass backward simulations. The area covered is also related to the location of the 16 cities under study.Species with an aerodynamic geometric mean diameter of 400 nm and geometric standard deviation of 1.6 were used to model the Secondary Sulfate aerosol transport. Generalized Tikhonov regularization was applied so as to acquire potential source areas and quantify their emission rate. The results acquired by this process indicate a significant source area for Secondary Sulfate on the East of the Caspian Sea. The maximum emission rate in that area is as high as 10 g m-2 s-1. Significant source areas also include South Poland and the Balkans. The results display many similarities to the SO2 emission map provided by ECLIPSE database. AcknowledgementsThis research has been funded by the program “RER/1/015 - Apportioning air pollution sources on a regional scale”, 2016 - 2017. ReferencesVratolis, S., Diapouli, E., Manousakas, M. I., Almeida, S. M., Beslic, I., Kertesz, Z., Samek, L., and Eleftheriadis, K.: A new method for the quantification of ambient particulate matter emissions, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-843, in review, 2023.
Glacier changes in Iceland since the Little Ice Age maximum - glacier outlines, terminus measurements and photographic evidence
Authors: Hannesdóttir Hrafnhildur , Sigurðsson Oddur , Guðmundsson Snævarr , Belart Joaquín M.C. , Þrastarson Ragnar H. , Pálsson Finnur , Magnússon Eyjólfur , Jóhannesson Tómas
Published: February 2023

A national glacier outline inventory for several different epochs since the end of the Little Ice Age (LIA) in Iceland has been created with input from several research groups and institutions, and has been submitted to the GLIMS (Global Land Ice Measurements from Space, nsidc.org/glims) database, where it is openly available. The glacier outlines have been revised and updated for consistency and the most representative outline chosen. The maximum glacier extent during the LIA was not reached simultaneously in Iceland, but many glaciers started retreating from their outermost LIA moraines around 1890. The total area of glaciers in Iceland in 2021 was ~10,300 km2. The total glacier area has decreased by ~2300 km2 since the end of the 19th century and by ~830 km2 since ca. 2000. During the first two decades of the 21st century, the decrease rate has on average been ~40 km2 a–1. In this period, some tens of small glaciers have disappeared entirely. Temporal glacier inventories are important for climate change studies, for calibration of glacier models, for studies of glacier surges and glacier dynamics, and they are essential for better understanding of the state of glaciers. Although surges, volcanic eruptions and jökulhlaups influence the position of some glacier termini, glacier variations have been rather synchronous in Iceland, largely following climatic variations since the end of the 19th century.  The glacier outlines are also available on a new glacier web portal (www.islenskirjoklar.is), together with measurements of frontal positions and mass balance and numerous photographs of glaciers at different times. The photographic glacier archive will be updated through systematic photographic surveys, including rephotography of historical photos, based on a collaboration of the Iceland Glaciological Society and Extreme Ice Survey. This website, which is intended for scientists, students and lay people alike, is a joint effort of institutions involved in glacier research in Iceland and the Iceland Glaciological Society. It will serve as a powerful tool for outreach on glacier and climate change in Iceland. The glacier inventory is planned to be updated every other year in the future as part of regular monitoring of glacier changes in Iceland. Furthermore, the larger ice caps will be divided into ice-flow basins along the ice divides of individual outlet glaciers determined from ice-surface DEMs, which will allow for more detailed analysis of area variations with time.
Overshoot proofing adaptation policies and plans
Authors: Yesil Burcu , Theokritoff Emily , Pringle Patrick , Menke Inga , Schleussner Carl-Friedrich
Published: February 2023

With 1.2°C current global warming, it becomes increasingly important to think about overshoot and what this would imply for adaptation. In the face of increasing impacts, more and more thresholds and limits to adaptation will be reached – but if global warming levels are brought down again through the deployment of negative emission technologies, what does this imply for adaptation?Here, we present a methodology which aims to provide concrete entry points for integrating overshoot risks into adaptation planning, with the objective of strengthening resilience, reducing vulnerability and avoiding maladaptation. We explore concepts such as impact (un)avoidability and (ir)reversibility, key elements of long-term adaptation planning. Ultimately, we aim to develop a step-based approach allowing adaptation planners to formulate and review adaptation policies adequately integrating the concept of overshoot and its implications.
Is multidecadal prediction of flood patterns possible for infrastructure planning purposes using the 10000 year cosmogenic isotope (10Be and 14C) record?
Authors: Asten Michael , McCracken Ken
Published: February 2023

We compare spectral decomposition of flood data from three sites in Australia (south-east coast, east-inland, east-central) with the Southern Oscillation Index (SOI), and with those from the Brahmaputra River (Bangladesh) and Nile River (Egypt). All show clear evidence of spectral maxima at medium periods approximating 50, 85, 130 and 200 years, which correspond closely to the maxima in the power spectra of the cosmogenic 10Be and 14C observations obtained from ice cores with ages covering the past 10000 years.  We find that the Gleissberg cycle (85 yr period) for Australian sites is out of phase with that for the Brahmaputra River.   All sites also show spectral maxima at short periods 6-20 yr as expected from the ENSO cycle; flood associations varying over these short periods are generally accepted. We explore the possibility that the medium periods can be used to assist in the prediction of flood and drought activity several decades into the future.  We consider   the hypothesis of a correlation or causal relationship existing between solar activity (including its effects on the intensity of galactic cosmic rays   on the Earth) and flood cycles for the medium periods.  The Australian SE coast and east-inland sites, and the Brahmaputra River, show strong medium-period maxima.  The phase of the medium periods is obtained by optimized fitting of multiple sine curves with periods obtained from the spectra; the Australian SE coast and east-inland sites show summed sine curves with high correlation.  The Brahmaputra River shows similar correlation at medium periods (in particular the Gleissberg 85-year period) but in opposite phase. The Australian east-central site (Murray-Darling Basin) and the Nile River (Egypt) show only weak evidence for the medium-period maxima which suggests ocean proximity is a factor for these influences.  The short duration SOI record shows   weaker evidence for medium-period spectral maxima, and the Southern Annular mode (SAM) and Indian Ocean Dipole (IOD) show no obvious correlation with observed medium-period flood patterns at the selected sites.  We speculate that the strong medium-period flood patterns are associated with the solar and/or cosmic ray cycles, observed in the cosmogenic record, where the causative mechanisms are yet to be established.  We conclude that the association of floods in medium-period cycles in addition to the association with the better-known short period variations associated with the ENSO cycle, provides opportunity for empirical predictions of flood patterns over ~80 years, and for the further investigation of possible causative mechanisms linking solar phenomena to oceanic indices and multi-decadal flood patterns.
Preliminary results for dune vegetation identification from high-resolution satellite imagery
Authors: Kombiadou Katerina , Costas Susana , Yang Zhicheng , Silvestri Sonia
Published: February 2023

Coastal dunes are important habitats that provide a variety of ecosystem services (ecological, economic, coastal protection, etc.) and, as such, their monitoring is a priority for environmental protection (i.e., EU Directives). Eco-geomorphologic feedbacks between dune plants and coastal topography are fundamental to the self-organisation capacity of coastal dunes and a shift in community structure and composition (i.e., expansion of invasive species) can cause a domino effect, potentially crippling previously established system adaption mechanisms. It follows that monitoring dune vegetation is crucial, especially in protected areas and in fragmented and stressed dune environments. Even though recent improvements in spectral and spatial resolution of satellite imagery open new and exciting prospects for large-scale environmental monitoring, this potential is largely unused in dune ecogeomorphology, due to the challenges related with the small size and density of dune plants and the complexity and heterogeneity of the existing species. Machine learning techniques and subpixel classification methodologies, like the Random Forest Soft Classification (RFSC), have shown promising results in similarly challenging environments in terms of plant size and heterogeneity, with high accuracies in subpixel fractional abundance of marsh-vegetation species. Even though subpixel classification could improve monitoring biodiversity from satellite imagery, similar approaches have never been tested for dune environments. These challenges and gaps inspired the present work, built around the idea of testing subpixel classification methods for dune plant species identification using high-resolution satellite imagery. Here we present preliminary results from the application of RFSC to the western barrier of the Ria Formosa system (S. Portugal) using WorldView2 (2017) imagery and training/validation samples from UAV, along with the next steps planned to test the hypothesis that RFSC methods can be successfully used to identify dune plant species and to assess their predictive capacity and identify potential limitations. Acknowledgements: The work was implemented in the framework of the DEVISE project (2022.06615.PTDC), funded by FCT (Fundação para a Ciência e a Tecnologia) Portugal. The authors acknowledge the project DUNES (52334), funded by ESA (European Space Agency), for the acquisition of the WorldView2 imagery used.
How a flood forecasting system saved lives and property in West Africa
Authors: Andersson Jafet C.M. , Ibrahim Aishatu T. , Soumahoro Ahmed Lamine , Fofana Vakaba , Ali Abdou , Arheimer Berit
Published: February 2023

Floods pose an increasing challenge for societies in West Africa; causing loss of lives, damaged infrastructure, and food insecurity. Improving flood management is hence paramount for the region, which several initiatives aim to contribute to. Hydrological forecasting systems can help, but only if they lead to appropriate action.This presentation focusses on how a flood forecasting system has been used to save lives and property in West Africa within the FANFAR project (www.fanfar.eu). The system was co-designed and co-developed together with hydrological services, emergency management agencies, river basin organisations, and regional expert centres in 17 countries. The pilot system was launched early in the project, producing new forecasts every day. This enabled operational staff at national and regional agencies to utilize the system during the current rainy season, for every season since 2019.During 2020, Nigeria experienced severe flooding. The Nigeria Hydrological Services Agency (NIHSA) hence decided to utilize FANFAR to warn the population of forthcoming flood risks, which resulted in 2 500 lives saved on one occasion, and minimisation of property damage on another. In the presentation we describe these events, and how NIHSA acted together with other institutions to entice action.FANFAR was also used in Ivory Coast during the 2022 rainy season. Operational staff at SODEXAM – the meteorological services of Ivory Coast – utilized the system to inform two flood-prone communities of forthcoming flood risks. This resulted in on-the-fly construction of a drainage ditch, which reduced impacts on the nearby community. In the presentation we describe the event and also the approach SODEXAM took to build trust and communicate with the communities.We also briefly describe the FANFAR system that employs a daily forecasting chain including meteorological reanalysis and forecasting based on HydroGFD, data assimilation of gauge observations, hydrological initialisation and forecasting with the HYPE model, flood severity assessment, and distribution through e.g. web visualisation. 
Influence of Hillslope Aspect on a Cinder Cone Evolution: The Sandal Divlit example, Kula, Turkey
Authors: Yetemen Omer , Avcioglu Aydogan , Ozcan Orkan , Simsek Ibrahim , Kolbuken Mesut , Yeo In-Young , Chun Kwok Pan , Gorum Tolga , Sen Omer Lutfi
Published: February 2023

Microclimatic variations in semi-arid ecosystems can cause topographic asymmetry over geologic time scales due to uneven distribution of incoming solar radiation as a function of slope aspect. This phenomenon has long been recognized in geomorphology and has been studied primarily in catchments with high spatial heterogeneity in climate forcing and underlying lithology. Due to fluctuations in prevailing climate and lithological differences in the studied catchments, the formation age and size of the catchments add another level of complexity and uncertainty. Due to their small size, uniform lithology, well-constrained initial morphology, and relatively young age, cinder cones are natural laboratories for better understanding the eco-hydro-geomorphic evolution caused by nonlinear interactions between vegetation, climate, and soil. The Sandal Divlit cinder cone located in the Kula volcanic field, western Turkey, is an inactive volcano and formed in the last stage of volcanism in the region. The climax vegetation in the primary succession following the volcanic eruption can be seen on north-facing slopes with trees. North-facing slopes have deeper soils than south-facing slopes, which have sparsely herbaceous plants and shrubs and thin, weakly developed soils. Airborne-LiDAR surveys and the digital elevation models having 5 m and 12.5 m spatial resolution were used to analyze the geomorphic descriptors and canopy structure of the cone as a function of aspect. In the summer and winter seasons, the surface temperatures of the cone were measured using a thermal-imaging drone. The results show that north-facing slopes are much cooler and have less evaporative demand than south-facing ones. As a result of denser vegetation attributed to relatively more available soil moisture, they are steeper than south-facing ones due to better erosion protection. Despite its young age (<30 ka), the cone has developed topographic asymmetry and is imprinted with the signature of aspect-related vegetation difference. This finding is further evaluated and with the results of landscape evolution models to assess the role of microclimate due to vegetation on the development of asymmetric geomorphological features.This study has been produced benefiting from the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not indicate that the content of the publication is approved in a scientific sense by TUBITAK.
Detailed characterization of biogeochemical processes in coastal aquifers: variations along the subterranean estuary-mixing zone at the MEDISTRAES experimental site
Authors: Almillategui Bella , Folch Sancho Albert , Rodellas Vila Valenti , Saaltink Maarten , Adan Alejandro , Tur-Piedra Jose , Ruiz-González Clara , Romano Gude Daniel , Diego Feliu Marc , Carrera Jesús
Published: February 2023

Coastal aquifers are characterized by their unique land-sea interaction and the main difficulty in studying these systems is the complexity of their biogeochemical cycles. Important processes in the “mixing zone” of coastal systems are associated with the ecosystem’s diversity, and supply and exchange of chemical compounds. This coastal body known as a “subterranean estuary” (STE), is characterized by a free connection to the sea, creating an interface between freshwater and seawater. The distribution and composition of substances flowing from land to sea change because the submarine groundwater discharges (SGD) considerably dilute the seawater that has invaded the aquifer through the free connection to the sea (SWI, Sea Water Intrusion).These processes were studied in an area 100 m long inland from the coastline and 30 m wide, in the alluvial aquifer of Argentona, Mataró, northeast of Barcelona, Catalonia (Spain). This experimental site was established in 2015 and has been equipped for intensive monitoring of coastal aquifer processes such as SWI and SGD. Currently, it is monitored with 25 piezometers (2 meters screened) consisting of 5 nests with 4 piezometers each (at 10m, 20m, 15m, and 25m intervals) and 4 individual piezometers. In this system described as a “multi-aquifer and reactive system”, we are characterizing the physicochemical and hydrogeochemical conditions associated with biogeochemical processes at different depths and seasonal variations. For this presentation, we will show new results of hydrogeochemistry, nitrogen isotopes, and microbiological parameters associated with different periods of monitoring that characterize the dynamics in the subterranean estuary. Acknowledgments: This work was funded by the Spanish Government (grant no. PID2019-110212RB-C21 and PID2019-110212RB-C22), the project TerraMar (grant no. ACA210/18/00007) of the Catalan Water Agency, and the SENACYT – IFARHU – BID Scholarship.
Resilience of productivity and water use of montane grassland in response to drought intensity under current and future climate conditions
Authors: Capponi Lisa , Neuner Gilbert , Still Christopher , Schaumberger Andreas , Herndl Markus , Bahn Michael
Published: February 2023

Multiple global change factors, such as elevated atmospheric CO2 concentrations, warming, and drought, are progressively affecting ecosystems worldwide. Future drought events will likely intensify, possibly leading to strongly non-linear threshold responses of ecosystem functioning. However, while of high ecological relevance, ecosystem responses to drought intensity have rarely been studied, and even less is known about whether future conditions involving a combination of elevated CO2 and warming can alter such responses. In an in-situ multifactor experiment in managed montane grassland, we studied the drought responses of ecosystem productivity, water use, and related canopy surface temperatures along with leaf-level stomatal conductance and photosystem II quantum yield. We analyzed whether and how resistance to and recovery from drought changed in response to drought intensity under current versus future (+300 ppm CO2, + 3° C) climate conditions. With increasing drought intensity, productivity and water use were increasingly reduced and were associated with increasing canopy temperatures, the effects being more pronounced in the future compared to current conditions. Our results suggest that the additional heat stress triggered by drought under future conditions can strongly reduce ecosystem resilience under scenarios of more extreme droughts.
Deep generative inversion of ERT data for electrical resistivity
Authors: Azevedo Leonardo , L. Pereira João
Published: February 2023

Electrical resistivity tomography (ERT) is a geophysical method used to imaging the subsurface and widely used in hydrogeological studies due to its sensitivity to electrical resistivity, which is directly related to rock type, porosity, ionic strength of the pore fluids, and surface conductivity of geologic materials. The prediction of subsurface properties from the recorded data at the surface requires solving a challenging geophysical inversion problem. For near-surface characterization studies, this is often accomplished with deterministic electrical resistivity inversion methods. Deterministic geophysical inversion approaches linearize the problem around an initial solution, resulting in a single smooth representation of the subsurface. Deterministic models are unable to capture the natural variability of the subsurface. Moreover, a single solution does not yield enough information for accurate uncertainty assessment. Contrary to deterministic approaches, stochastic inversion methods predict multiple model realizations that fit similarly the recorded geophysical data and allow assessing uncertainties. Lately, deep learning algorithms based on deep generative models have been used to re-parametrize model and data spaces into low-dimensional domains and solve geophysical inverse problems in a more efficient way.We propose an ERT inversion methodology in which a deep convolutional variational autoencoder (VAE) network is trained with a set of electrical resistivity models generated using geostatistical simulation. After training the VAE, the latent space is perturbed and updated iteratively with adaptive stochastic sampling to generate electrical resistivity models by inputting the optimized latent vectors to the decoder part of the VAE. From the set of decoded models, we use a finite volume approximation of Poisson’s equation to compute synthetic apparent resistivity models. The misfit between predicted and observed apparent resistivity data is used to drive the convergence of the iterative procedure and condition the optimization of new models in the subsequent iterations.The proposed methodology is illustrated by applying it to both a two-dimensional synthetic case and to a two-dimensional profile obtained from an ERT survey carried out in an area located in the Southern region of Portugal. In both application examples, the predicted models generate synthetic geophysical data that match the observed one. We show the ability of the model to assess spatial uncertainty and compare the results obtained in the real data set against commercial deterministic ERT inversion methodology.The work presented herein is supported by the PRIMA programme under grant agreement No. 1923, project Innovative and Sustainable Groundwater Management in the Mediterranean (InTheMED). The PRIMA programme is supported by the European Union.
Seasonal Variation of Simulated Carbonaceous Fine Particulate Matter overthe Indian Region by using WRF-Chem with two emission Inventories:EDGAR-HTAP and SAFAR-2018
Authors: Kumar Praveen
Published: February 2023

Seasonal Variation of Simulated Carbonaceous Fine Particulate Matter overthe Indian Region by using WRF-Chem with two emission Inventories:EDGAR-HTAP and SAFAR-2018Praveen Kumar1, Gufran Beig1,4, Vikas Singh2, B.S. Murthy1, B.R. Bamniya31Indian Institute of Tropical Meteorology, Pune- 4110082 National Atmospheric Research Laboratory, Gadanki, AP-5171123Mohan LalSukhadiya University, Udaipur, 3130014National Institutes of Advanced Studies (NIAS), Indian Institute of Science (IISc) Campus,BANGALORE-560012Abstract:This study better evaluates Black Carbon (BC) using Weather Research and Forecasting modelcoupled with chemistry (WRF-Chem) v3.9.1.1, with newly developed emission inventorySAFAR-2018 and global one EDGAR-HTAP for the year 2018. The simulation provides a viewof the seasonal and regional pattern BC concentrations, confirmed by comparing surfacemeteorological parameters and BC concentrations to the MERRA reanalysis for the Indianregion. It found that the model simulated surface C-PM concentration with SAFAR-2018emission inventory is slightly overestimated, but simulation with EDGAR emission inventory isunder-estimated than MERRA. It also found that the model-simulated meteorological parameters( e.g., wind speed at 2 m, the surface temperature at 2 m, and Planetary Boundary Layer heightshowed better agreement with observation. Compared to the simulation with EDGAR emissioninventory, simulated geographic patterns of seasonal mean BC with SAFAR-2018 emissioninventory exhibit good agreement with MERRA. In the IGP region, the concentration of BCshowed the highest peak during the winter, followed by the post-monsoon season compared toother subcontinents of India. The correlation coefficients of annual hourly time series of surfaceBC_sf (SAFAR-2018 emission) concentrations with MERRA over India were higher (0.92) withRMSE 0.45. These correlations were higher than those (EDGAR emission) observed for thesurface BC_ed (R = 0.91 & RMSE = 0.48) concentrations. It appears that model simulation withSAFAR-2018 emission inventory well-captured pattern and magnitude over the Indian region,increasing magnitude of BC concentrations may help to quantify better the effect on climate andatmospheric condition over the Indian region.
Quantifying the Wet Deposition of Reactive Nitrogen over China: Synthesis of Observations and Models
Authors: Tan Jiani , Su Hang , Itahashi Syuichi , Tao Wei , Wang Siwen , Li Rui , Fu Hongbo , Huang Kan , Fu Joshua , Cheng Yafang
Published: February 2023

Accurate estimation on reaction nitrogen (Nr) deposition is highly demanded for assessing the impacts on the environment and human beings. This study investigated the wet deposition of inorganic nitrogen (IN) in mainland China by measurements from over 500 sites from five observational networks/databases and ensemble results of eleven chemical transport models (CTMs). Each data source has its focus and limitations and together formed a comprehensive view over China. But the inconsistency among different sources may hinder the appropriate usage of data. Model evaluation results demonstrated the models’ deficiency in simulating the wet NO3- deposition over Southeast China (40% underestimation) and showed an overall underestimation of wet NH4+ deposition over the hotspot regions (5-60% underestimation). A synthesis of this study and twelve reference studies was conducted to quantify the national amount of wet IN deposition. The estimations by CTMs ranged 2.4-3.9 Tg(N) yr-1 for wet NOy deposition and 4-6.7 Tg(N) yr-1 for wet NHx deposition, after adjusting the results with 10-19% underestimations in wet NOy deposition and 1-40% underestimations in wet NHx deposition. The estimations by ground observations ranged 7.1-9 Tg(N) yr-1 for wet NOy deposition and 8-13.1 Tg(N) yr-1 for wet NHx deposition, which were 20-275% higher than the estimation by CTMs, but the results were strongly influenced by the abundances and representative of measurements. Studies using statistical techniques to interpolate site observations predicted 3-5.5 Tg(N) yr-1 for wet NOy deposition and 3.9-7.2 Tg(N) yr-1 for wet NHx deposition. This approach benefited from high accuracy and good robustness of the statistical models, but the uncertainty in the interpolation methods could be a potential drawback.
A seamless hydrologic forecasting system for Germany
Authors: Najafi Husain , Oldrich Rakovec , Shrestha Pallav Kumar , Thober Stephan , Samaniego Luis
Published: February 2023

An experimental hydrological forecasting system has been developed for Germany (https://www.ufz.de/HS2SForcasts4Germany) at high resolution (1 km). Since early 2021, the hydrological forecasting system provides operational ensemble forecasts for soil moisture droughts at sub-seasonal time scale (HS2S). In the next year, it will be upgraded to streamflow and inundation areas. The mesoscale Hydrologic Model (mHM- www.ufz.de/mhm) with the Multiscale Parameter Regionalization scheme [1,2,3] is used to simulate hydrological forecasts across German catchments. This model is forced with the extended large atmospheric ensemble forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF). The soil moisture index is updated twice per week with associated uncertainties of the initial atmospheric conditions. The initial conditions are obtained with the DWD precipitation and temperature data, similar to the German Drought Monitor (www.ufz.de/droughtmonitor). The hydrological forecasting system was also evaluated for 2021 summer flood in west Germany [4]. The system has shown promising results in flood forecasting as well. This system is based on the EDgE system [5] and can easily be developed across other regions around the world.Refrences[1] Samaniego L., Kumar R., & Attinger, S. (2010). Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523, doi:10.1029/2008WR007327. WRR Editors' Choice Award 2010[2] Samaniego L., et al. (2021). mesoscale Hydrologic Model. Zenodo. doi:10.5281/zenodo.1069202, https://doi.org/10.5281/zenodo.1069202[3] Kumar, R., Samaniego, L., & Attinger, S. (2013). Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resour. Res., 49(1), 360-379. https://doi.org/10.1029/2012WR012195.[4] Najafi, H., Rakovec, O., Kumar Shrestha, P., Thober, S., & Samaniego, L. (2022). Post-Assessment of ECMWF-mHM ensemble flood forecasting for 2021 summer flood in west Germany. 2022 AGU Fall meeting. Chicago, IL & online everywhere.[5] Samaniego et al. (2019). Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe. BAMS, 100(12), 2451–2472. https://doi.org/10.1175/BAMS-D-17-0274.
Assessing and reducing stratigraphic uncertainty in the subsurface: where are we standing?
Authors: Caumon Guillaume , Herrero Julien , Bodin Thomas , Baville Paul
Published: February 2023

Sedimentary strata are essential archives of the past conditions of the earth, and host significant natural resources in the subsurface. However, inferring the features of strata at depth (e.g., geometry, connectivity, physical or geological properties), remains a challenge prone to many uncertainties. Classically, the layers and their geometry are first interpreted from boreholes, geological outcrops and geophysical images, then layer properties can be addressed with geostatistical techniques and inverse methods. Theoretical models considering horizon depth uncertainty have been proposed decades ago, and geostatistical simulation can sample petrophysical uncertainties, but these approaches leave the number of layers fixed and are rely on conformable layering assumptions which are seldom met. We review some recent developments in well correlation in the frame of relative chronostratigraphy, which addresses the problem of locating potential gaps in the stratigraphic record. We also present some first results of the integration of the number of layers in inverse problems using a reversible jump Monte Carlo method. These two elements open interesting perspectives to jointly address topological, geometrical and petrophysical uncertainties at multiple scales in sedimentary basins. Although such uncertainties can have significant impact on quantitative geological and geophysical model forecasts, many computational challenges still lie ahead to appropriately sample uncertainties. Harnessing these challenges should open the way to finding, on a case-by-case basis, the suitable level of detail between detailed stratigraphic architectures and effective medium representations.
Signatures of the subduction/obduction processes in the lithosphere and asthenosphere beneath the Semail Ophiolites in Oman revealed by seismic anisotropy
Authors: komeazi Abolfazl , Kaviani Ayoub , Rümpker Georg , Weidle Christian , Meier Thomas
Published: February 2023

The obduction of the Semail Ophiolite onto the Arabian continental margin during the convergence of the Arabian and Eurasian plates has left a significant impact on the lithospheric structure beneath the Oman Mountains. However, there remains a degree of uncertainty concerning the extent to which the inherited structures (pre-existing features of the lithosphere) contribute to the obduction of ophiolites. To gain a deeper understanding of the impact of the obduction process on the mantle structure beneath northern Oman, we analyze seismic anisotropy beneath this region using splitting analysis of teleseismic shear wave data collected from a dense network of 40 seismic stations that have been operational for approximately 3 years since 2013. 

Based on azimuthal distribution of the shear wave splitting (SWS) parameters, φ and δt, we are able to divide the study area into two subregions. The stations located to the west of the Semail gap exhibit relatively azimuthally invariant SWS parameters suggesting a single anisotropic layer. On the other hand, at most of the stations located in the central and eastern regions we observe a 90-degree periodicity versus back-azimuth, indicative of a depth-dependent anisotropic medium. 

In the western part, the fast axes are aligned with the strike of the collision between the continental and oceanic plates, where the oceanic lithosphere is believed to be obducted over the continental lithosphere. We also invert the azimuthal variation of the SWS parameters from the central and eastern stations for two layers of anisotropy. The fast axes of the upper layer exhibit a predominantly NW-SE trend, in good agreement with the anisotropy directions of the one-layer models obtained in the western region. The fast axes of the lower layer display a NE-SW trend, possibly representative of the large-scale mantle flow resulting from the present-day plate motion. 
Deep Learning for volcanic risk assessment
Authors: Corradino Claudia , Cariello Simona , Torrisi Federica , Amato Eleonora , Zago Vito , Del Negro Ciro
Published: February 2023

The large amount of lava outflows during effusive eruptions can cause profound morphological changes, affecting both the natural and inhabited environment, destroying buildings, agricultural fields and important infrastructures such as roads, power lines, aqueducts and even modified the coastline. The ongoing demographic congestion around volcanic structures increases the potential risks and costs that lava flows represent and leads to a growing demand for implementing effective risk mitigation measures. Therefore, it is important to assess the elements at risk in volcanic areas to establish the mitigation actions to reduce the lava flow risk. Risk management for volcanoes is not just an emergency response to save lives but is also important in terms of economic loss. However, the collection of data regarding exposed elements surrounding the volcanoes is a lengthy and time-consuming process but utilizing the satellite images together with several machine learning techniques helps address this goal. We propose a cloud based platform in Google Colab using Land Use and Land Cover (LULC) classifiers to automatically assess the elements at risk by exploiting freely available high spatial resolution satellite images. This procedure allows to get an updated map of elements at risks in volcanic areas worldwide and will allow to routinely update the exposure map and thus risk map. In fact, up-to-date risk maps are fundamental to reaching the optimal decision in case of any hazard and crisis and can help us add or delete critical zones around the volcano. Using the freely available Sentinel 2-Multispectral Instrument (MSI) images and deep learning models, we aim to test the LULC applicability to a variety of volcanic areas whilst comparing the performances of two Convolutional Neural Network (CNN) architectures, namely VGG16 and ResNET50.
Low-cost in-situ sensor networks for soil moisture and water table measurements: experiences and recommendations.
Authors: Briciu-Burgina Ciprian , Zhou Jiang , Ali Muhammad Intizar , Regan Fiona
Published: February 2023

Soil moisture is an essential parameter for irrigation management, transport of pollutants and estimation of energy, heat, and water balances. Soil moisture is one of the most important soil spatial-temporal variables due to the highly heterogeneous nature of soils which in turn drives water fluxes, evapotranspiration, air temperature, precipitation, and soil erosion. Recent developments have seen an increasing number of electromagnetic sensors available commercially for soil volumetric water content (θ) and their use is expanding providing decision support and high-resolution data for models and machine learning algorithms.In this context, two demonstrations of in-situ LoRaWAN sensor networks are presented. The 1st one is from a grassland site, Johnstown Castle, Wexford Ireland where a network of 10 low-cost soil moisture (SM) sensors has been operating for 12 months. The 2nd network has been operating for 6 months at a peatland site (Cavemount Bog, Offaly, Ireland) which is currently undergoing a rehabilitation process through re-wetting. At this site, in addition to SM sensors, ultrasonic sensors are used for continuous measurement of the water table at 7 locations. For both sites, the analytical performance of the SM sensors has been determined in the laboratory, through calibrations in liquids of known dielectric permittivity and through field validation via sample collection or time domain-reflectometry instrumentation (TDR). Experiences and recommendations in deploying, maintaining, and servicing the sensor networks, and data management (cleaning, validation, analysis) will be presented and discussed. Emphasis will be placed on the key learnings to date and the performance of the low-cost sensor networks in terms of collected data.Small-scale sensor networks like these are expected to bridge the gap between the low spatial resolution provided by the satellite-derived products and the single point/field measurements. Within the project, the sensor network will provide spatial observations to complement existing fixed point measurements. It will allow researchers to investigate SM dynamics at field scale in response to different soil types, soil density, elevation, and land cover.
Biogeocaching - a scavenger hunt for the treasures of biology around Lake Lunz
Authors: Hödl Romana , Attermeyer Katrin , Coulson Laura , Harjung Astrid
Published: February 2023

Climate change and decreasing biodiversity are currently hot topics in the media. Freshwaters in the alpine region are good indicators of climate change and, hence, perfect examples for illustrating these threats. Here, we want to share our idea for a Geocaching path (similar to the popular treasure hunt game) that is used to educate the public about the biology of freshwaters. We want to educate the visitors about the natural environment and the consequences of climate change and decreasing biodiversity for our aquatic ecosystems and livelihoods. In particular, we want to show the approaches of scientists to understand and predict these threats and, furthermore, how our society can find solutions to protect aquatic ecosystems. Lake Lunz is a very popular place for tourists. Visitors enjoy walks around the lake as well as swimming. Close by is also one of the oldest lake research stations (WasserCluster Lunz - Biologische Station), where scientists from all over the world are currently conducting on aquatic ecosystems. The project received funding from the EGU Public Engagement Grant in 2019. The GPS coordinates for the Geocache (a small treasure box in an insect hotel) are hidden in the answers to several questions about freshwater biology that lead the participants around the lake, a search we termed "Biogeocaching". The answers can be found on different informational signs that are set up around the lake and at the experimental sites and research facilities of WasserCluster Lunz. After finishing the path, the participants will have learned about ecology of alpine lakes and the research activities at WasserCluster Lunz. We think that geocaching as a treasure hunt is a playful way for people of all ages to discover nature. The combination of an outdoor recreational activity with information about freshwaters, climate change, and decreasing biodiversity -Biogeocaching - will sensitize the public to and raise awareness of these hot topics in the field of Earth Sciences. We hope to encourage other researchers and research institutes to develop something similar on their topic and research.