bluuebunny/crossref_metadata_2025 huggingface dataset:
The Atmospheric effects of Southern Ocean open-ocean polynyas onto coastal polynyas in EC-Earth3
Authors: Gunnarsson Jakob , Zhou Lu , Heuzé Céline
Published: February 2023

Polynyas are recurrent areas of open water or thin ice within the ice pack, which alter the local heat and moisture exchange and high-latitude atmosphere-ocean circulation interannual variability. They are differentiated as coastal (latent heat) or open-ocean (sensible heat) polynya according to their forming location. Especially, coastal polynyas are critical sources of dense water and the formation of Antarctic Bottom Water (AABW) following the brine enrichment of surface waters during sea-ice formation, and easily influenced by the local atmosphere conditions. However, few studies have examined the atmospheric response of open-ocean polynyas on the coastal polynyas given the fact that open-ocean polynyas have capability to re-adjust mesoscale atmosphere circulation. To better understand the surrounding impact of large open-ocean polynya events, output from CMIP6 historical experiment synoptic scale EC-Earth3 is adopted. Our results show an increasing coastal polynya frequency and extent accompanying with more active open-ocean polynya years in the Weddell Sea. The results are explained by near-surface wind speed differences in the coastal regions, which are found statistically significant between more and less active open-ocean polynya years. Furthermore, those intensifications of winds are found in days where easterly-dominated winds north-westerly to north-easterly and easterly to south-easterly cross the open-ocean polynya. Increased near-surface air temperatures as well as a deepening in sea level pressure are also observed during the years with more active open-ocean polynya events. The findings contribute to a better understanding of coastal polynya opening processes, as well as how we might expect to see the different type of polynya interact by their influence and dependence on surrounding atmospheric conditions.
Spatial modelling of vineyard erosion using machine learning methods
Authors: Takáts Tünde , Mészáros János , Albert Gáspár , Pásztor László
Published: February 2023

Sustainable agriculture is seriously threatened by severe soil erosion, which is also occurred in the Neszmély Wine Region, in the northern part of the Gerecse Hills in Hungary. In the region, three vineyards with visible signs of erosion were chosen to quantify the amount of eroded soil. The empirically based Universal Soil Loss Equation (USLE) model was utilized first to determine the soil loss. The study sites were monitored with an unmanned aerial vehicle (UAV) to create high-resolution models of seasonal and annual soil loss. After the empirically based, spatially detailed quantification of erosion, we have tested the applicability of machine learning methods to predict soil erosion for the selected parcels during the same time period. The primary concept was to use the empirically inferred erosion values as observation data to construct parcel-specific prediction models and test them on the remaining two parcels. In the model we have used (i) Sentinel 2 satellite data in the form of both native spectral bands and its derived spectral indices; (ii) terrain features derived from digital surface model created and aggregated from the UAV flights and (iii) formerly elaborated digital soil property maps as auxiliary data. Various machine learning methods (ranger, ridge, xgbLinear, enet, pls, brnn) have been tested to find the best performing predictions. Observation data were generated in the form of random points, in 100 representations. Model performances have been tested by proper measures to evaluate the applicability of the applied machine learning techniques for soil erosion mapping. Acknowledgment: Our research has been supported by the Hungarian National Research, Development and Innovation Office (NRDI; Grant No: K 131820).
Modeling Intensity-Duration-Frequency curves for the whole range of precipitation
Authors: Haruna Abubakar , Blanchet Juliette , Favre Anne-Catherine
Published: February 2023

Intensity-Duration-Frequency curves are useful in water resources engineering for the planning and design of hydrological structures such as sewer lines, culverts, drains, dams, dykes.  They provide the mathematical link between the rainfall intensity, I, over a given duration, D, that is expected to be exceeded on average, once every T years (frequency). As opposed to the common use of only extreme data to build IDF curves, here, we use all the non-zero rainfall intensities, thereby making efficient use of the available information. As a parametric model, we use the Extended Generalized Pareto Distribution (EGPD) of Naveau et al. (2016)  for the non-zero intensities. We consider three commonly used approaches for building IDF curves. The first approach is based on the scale-invariance property of rainfall, the second relies on the general IDF formulation of Koutsoyiannis et al. (1998) and the last approach is purely data-driven (Overeem et al., 2008), where the linkage of parameter and duration is empirically determined from data. Using these three approaches, and some extensions around them, we build a total of 10 models for the IDF curves. We then compare them based on their in-sample performance, parsimony in parameterization, as well as their robustness and reliability in a split-sampling cross-validation framework. We consider a total of 81 stations at 10 min resolution in Switzerland.  As a result of the marked seasonality of rainfall in the study area, we adopted a seasonal-based analysis.  The results reveal that the model based on the data-driven approach is the best model. It is able to correctly model the observed intensities across duration while being reliable and robust. It is also able to reproduce the space and time variability of extreme rainfall across Switzerland. While our study focused on Switzerland, the results can be generalized everywhere, especially for locations with high-resolution data availability. To our knowledge, our work is the first to consider using the EGPD in IDF curve modeling.  ReferencesKoutsoyiannis, D., Kozonis, D., & Manetas, A. (1998, April). A mathematic cal framework for studying rainfall intensity-duration-frequency relationships. Journal of Hydrology, 206 (1-2), 118–135. Retrieved 2021-09-06, from https://linkinghub.elsevier.com/retrieve/pii/S0022169498000973 doi: 10.1016/S0022-1694(98)00097-3Naveau, P., Huser, R., Ribereau, P., and Hannart, A.: Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection, Water Resour. Res., 52, 2753–2769, https://doi.org/10.1002/2015WR018552, 2016.Overeem, A., Buishand, A., & Holleman, I. (2008, January). Rainfall depth duration-frequency curves and their uncertainties. Journal of Hydrology, 348 (1-2), 124–134. Retrieved 2021-11-30, from https://linkinghubelsevier.com/retrieve/pii/S0022169407005513 doi:10.1016/j.jhydrol.2007.09.044
Climate change impacts on winds in Europe: do global and regional climate models tell the same story?
Authors: Wohland Jan
Published: February 2023

Wind energy is essential in many decarbonization strategies and potentially vulnerable to climate change. While existing wind climate change assessments rely on regional or global climate models, a systematic investigation of the global-to-regional climate modeling chain is missing. In this presentation, I therefore address the differences in climate change impacts on winds according to  regional and global climate model ensembles under three different future scenarios. I highlight two key limitations, namely (a) the differing representation of land-use change in global and regional climate models which compromises comparability, and (b) the consistency of large-scale features along the global-to-regional climate modeling chain. To this end, I analyze the large EURO-CORDEX ensemble (rcp85: N=49; rcp45: N=18; rcp26: N=22) along with the driving global models (rcp85: N=7; rcp45: N=5; rcp26: N=7), finding evidence that climate change reduces mean wind speeds by up to -0.8 m/s (offshore) and -0.3 m/s (onshore). Moreover, I provide physical explanations for these changes by identifying two key drivers. First, onshore wind speeds drop in the driving global models in regions and scenarios with strong land use change but show no drop in EURO-CORDEX where land use is held constant. Second, offshore wind reductions follow decreases in the equator-to-pole temperature gradient remarkably well with correlations reaching around 0.9 in resource-rich European countries like Ireland, the United Kingdom and Norway, implying that arctic amplification is a severe risk for European offshore wind energy. My results suggest that earlier conclusions of negligible climate change impacts on wind energy might be premature if either land use changes strongly or polar amplification is at or above the range sampled in global climate models. In conjunction with earlier work that demonstrated the relevance of multidecadal wind fluctuations caused by climate variability, these results call for a better inclusion of climate risk in wind energy planning. Reference Wohland, J. Process-based climate change assessment for European winds using EURO-CORDEX and global models. Environ. Res. Lett. (2022) doi:10.1088/1748-9326/aca77f.
Using outdoor radon and radon flux to predict areas with high radon risk
Authors: Baumann Sebastian , Gruber Valeria , Peterman Eric , Cinelli Giorgia
Published: February 2023

Radon is a radioactive noble gas built in the uranium – radium decay chain. Accumulated indoor radon concentrations can cause lung cancer. The reduction of indoor radon concentrations is a health political topic, noticing indoor radon is a large source of radiation exposure. The delineation of areas with high radon risk is an essential task to effective implement radon protection measures. The methods for delineation range from aggregate statistics of indoor radon concentrations to data driven machine-learning techniques with multiple predictors.The main factors determining indoor radon concentrations are geogenic parameters (e.g. uranium content, permeability of the soil), building characteristics (e.g. sealing against the underground) and using habits (e.g. air exchange rate). Radon is not only a radiation protection topic. Outdoor radon and radon flux is used in atmospheric sciences as tracer for greenhouse gases and as input variable for atmospheric modelling.We investigate the possibility using outdoor radon and radon flux to predict areas with high radon risk, by comparing these parameters with other parameters used for radon risk prediction as geological information, uranium content of the soil or weather data. We use the gridded indoor radon concentrations of the European Atlas of Natural Radiation as basis to define if an area shows high indoor radon concentrations. We perform a correlation analysis of the above-mentioned parameters. Further, we predict the gridded indoor radon concentrations with a random forest model and calculate feature importance for the selected model to investigate which parameters have the most impact on the prediction.This research is part of project 19ENV01 traceRadon.  The project 19ENV01 traceRadon has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
Are Global Drylands Self-Expanding?
Authors: Koppa Akash , Keune Jessica , Miralles Diego G.
Published: February 2023

Aridification threatens not only water availability but also adversely affects ecosystem health, and energy security. Using the (atmospheric) aridity index (AI) – defined as precipitation, (P) over potential evaporation (Ep) – several studies have shown that global drylands are either expanding or will expand in the future. Expansion is defined as the reduction of AI below 0.65, i.e., a change from a humid to a dry region may be owed to deficits in P and/or increases in Ep. However, the actual mechanisms and processes driving dryland expansion remain less explored. Here, we use an observationally-constrained Lagrangian transport model to test if expansion of drylands is self-fuelled: can reductions in moisture transport from existing drylands result in aridification of existing humid regions and thus lead to dryland expansion?To estimate the spatial extent of drylands, we calculate AI using P from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) (Beck et al 2019) and Ep from the hPET dataset (Singer et al. 2021). To quantify the changes in moisture and heat transport into newly expanded drylands, we use global simulations of the FLEXPART version 10.4, forced with the ERA-Interim reanalysis for a period of 38 years (1981–2018). The FLEXPART outputs include the properties of the air parcels at 3-hourly time steps, which are then post-processed using the Heat and Moisture Tracking Framework (HAMSTER v1.2.0) described by Keune et al. (2022) and bias-corrected using evaporation from the GLEAM-Hybrid dataset (Koppa et al. 2022).Preliminary results show that between 1981 and 2018, ~5.5 million km2 of the terrestrial land surface underwent aridification (humid to dryland transition). Further, our results indicate that, on an average, ~45% of the reduction in AI can be attributed to reduction in P, out of which ~32% can be traced to reduction in moisture transport from existing drylands. Preliminary findings support our hypothesis that drylands are indeed self-expanding. References:Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., van Dijk, A. I. J. M., McVicar, T. R., & Adler, R. F. (2019). MSWEP V2 Global 3-Hourly 0.1° Precipitation: Methodology and Quantitative Assessment, Bulletin of the American Meteorological Society, 100(3), 473-500.Keune, J., Schumacher, D. L., & Miralles, D. G. (2022). A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models. Geoscientific Model Development, 15(5), 1875–1898. doi:10.5194/gmd-15-1875-2022.Koppa, A., Rains, D., Hulsman, P., Poyatos, R., & Miralles, D. G. (2022). A deep learning-based hybrid model of global terrestrial evaporation. Nature Communications, 13(1), 1912. doi:10.1038/s41467-022-29543-7.Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., … Michaelides, K. (2021). Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981-present. Scientific Data, 8(1), 224. doi:10.1038/s41597-021-01003-9
Using atmospheric models to simulate backward certain gases that are the result of illegal activities and locate the source
Authors: Mantsis Damianos , Gialampoukidis Ilias , Vrochidis Stefanos , Tsikrika Theodora , Kompatsiaris Ioannis
Published: February 2023

Illegal activities such as the manufacturing of home-made explosives may result in the dispersion of certain type of gases in the atmosphere or water pollutants. Our study addresses the methodology that can be used to track the source location of these gases after they have been detected. Traditionally, tracking the source location of a gas release requires the knowledge of the emission maps, however, given the nature of the task, this is unknown in our case. Our methodology, does not involve inverse modeling, and only requires the use of a network of instruments on the ground or mounted on aerial vehicles. The FLEXPART-WRF Lagrangian dispersion model is used to backward simulate the dispersion and transport of the gases at 0.5-1 Km horizontal resolution. The numerical experiments take place at two different geographical regions, i.e. one with strong topography and another over plain terrain with no topography, and over a wide range of meteorological conditions. Our results indicate that 5 to 10 ground measurements are enough to locate the source with an accuracy of a few kilometers. Identifying the time of the release, on the other hand, is more challenging especially if the initial release of the gas does not take place instantly and is gradual.
Dual boundary coordinates in polar magnetosphere-ionosphere studies
Authors: Burrell Angeline , Chisham Gareth , Zawdie Kate
Published: February 2023

The high latitude ionosphere, which coincides with the Arctic and Antarctic regions, is a complex region that is strongly coupled with the magnetosphere, neutral atmosphere, and the solar wind.  The high latitude ionosphere may be divided into two regions based on the portion of the magnetosphere to which the ionosphere is connected.  The most poleward region, the polar cap, is the area characterized by open magnetic field lines that connect directly to the interplanetary magnetic field (IMF) instead of closing in the opposite hemisphere.  Within the polar cap, ionospheric plasma moves anti-sunward and HF propagation paths between a transmitter and receiver may occur through reflection in either the E region or F region of the ionosphere. Just equatorward of the polar cap is the auroral oval, a region that experiences high amounts of particle precipitation and energy transfer between the magnetosphere and ionosphere along closed magnetic field lines.  The equatorward edge of the auroral oval marks the beginning of the mid-latitudes.  Defining high latitude coordinates relative to these physically significant boundaries has implications for statistical studies, modeling applications, and research combining magnetospheric and ionospheric data.  This study explores the impact of using single or multiple boundaries on such high latitude research efforts, and presents a tool to aid this research.
Real-time gradual leakage detection system for water distribution networks based on MIMO-ANN
Authors: Wan Xi , Farmani Raziyeh , Keedwell Edward
Published: February 2023

Leakage detection is a critical issue in water management for water distribution systems (WDSs). With the availability of real-time monitoring data, leakage detection for WDSs based on data-driven methods has received increasing attention in recent years. Current data-driven leakage detection methods are based on a single-step prediction model that only focuses on burst events that are characterized by sudden changes in flow or pressure data in a very short time. However, gradual leakage events that develop from small seeps to noticeable leaks could last for weeks or even months, and these gradual events will cause more water loss and do more harm to the WDS. Furthermore, the gradual leakage events are more challenging to be detected due to its slowly changing pattern. Therefore, this work presents an early warning system for gradual leakage events based on a multistep forecasting strategy. A multi-input multi-output (MIMO) artificial neural network (ANN) is developed to capture the diurnal, weekly and seasonal patterns in the flow monitoring data. The generated forecasting vector is further compared with the observed measurements based on the cosine distance. The residual vector is further analyzed by exponential weighted moving average (EWMA) to smooth the spikes and noises. The final statistics are then used to raise alarms for the monitoring data. The method has been applied to a hypothetical town called L-Town to demonstrate its applicability. The results showed that the proposed method is capable of detecting gradual leakage events with a very small growth rate. In addition, all gradual leakage events are detected with short detection time, high detection accuracy, and low false alarms.
Close-range methods for muon imaging applications: a case study from Italy
Authors: Beni Tommaso , Borselli Diletta , Bonechi Lorenzo , Lombardi Luca , Gonzi Sandro , Ciaranfi Roberto , Bongi Massimo , Ciulli Vitaliano , Fanò Livio , Frosin Catalin , Paccagnella Andrea , Melelli Laura , Turchetti Maria Angela , D'Alessandro Raffaello , Gigli Giovanni , Casagli Nicola
Published: February 2023

The employment of remote sensing (RS) survey methods, in particular of close-range methods, as part of the muon imaging process is becoming a topic of growing interest. Use of light detection and ranging (LiDAR) methodologies, like terrestrial laser scanner (TLS), together with the unmanned aerial vehicles digital photogrammetry (UAV-DP) and satellite data are proving to be fundamental tools to carry out a reliable muographic measurements campaign. The main purpose of this presentation is to show the importance of correctly plan TLS and UAV-DP field surveys for muon radiography applications. To this aim, a real case study is presented: the research of hidden tombs at the Volumni Hypogeum archeo-geosite (Umbria, Italy). A high-resolution digital terrain model (DTM) and three-dimensional models of the surface/sub-surface were created merging different RS survey methods. The muon flux transmission was measured using the MIMA detector prototype (Muon Imaging for Mining and Archaeology). The latter is a small tracker (0.5 x 0.5. x 0.5 m3) developed by the physicists of the National Institute of Nuclear Physics (INFN), unit of Florence, and the Department of Physics and Astronomy of Florence. The measured muon flux was compared to the simulated one, obtained using the three-dimensional created environment, to infer information about the average density of the studied target along the various LoS (line of sight). The study highlights the importance of correctly carrying out the TLS and UAV-DP survey to make reliable hypotheses and decisions throughout the muographic measurement campaign. Furthermore, we pointed out how the precision of the tridimensional data can bias the muon imaging results.
Surface uplift of the Eastern Alps. Much faster than we thought?
Authors: Stüwe Kurt , Gradwohl Gerit , Robl Joerg , Plan Lukas , Fabel Derek , Stuart Fin
Published: February 2023

We present cosmogenic nucleide data that help to understand the ill-constrained  uplift history of the Eastern Aps. Well accepted, but indirect evidence  for this uplift history includes: (a) the onset of flexural subsidence of the foreland basins, or (b) the formation of the Periadriatic line (recording the onset of continent-continent collision in the Alps). Both are often used to suggest about 30 Ma as the starting date for the surface uplift of the range. Since this time the fine interplay of many kilometres of upwards rock uplift and downwards erosion resulted in net surface uplift of some 2-3 kilometres but reference frames that allow to discern between rock uplift and surface uplift are often hard to identify. One way of measuring surface uplift rates is through the study of areas where erosion did not occur. That is, dating and identifying relicts of ancient base levels for example in caves, sediments or paleosurfaces.In this contribution we present 10Be, 21Ne, 26Al cosmogenic nucleide data of fluvial sediments sampled in some 50 caves across the Eastern Alps from elevations between 300 and 2500 m surface elevation. We collected samples that were interpreted to have been deposited during cave formation at the vadose-phreatic transition. As such, they form markers for base level and  the age of their burial into the cave may be interpreted as the time the cave was at base level some few hundreds of meters above sea level. Interpretation of our data indicates that the uplift rate of the Eastern Alps may be in the order of 200 m – 500 m per Million years for much of the Pliocene. As such, much of the observed surface uplift of the Eastern Alps may have occurred since the late Miocene and surface uplift is thus much faster than previously thought. 
Carbon isotope and biostratigraphic evidence for an expanded PETM section in the deep Gulf of Mexico: implications for landscape response to climate change from source to sink
Authors: Castelltort Sebastien , Vimpere Lucas , Spangenberg Jorge , Roige Marta , Adatte Thierry , De Kaenel Eric , Fildani Andrea , Clark Julian , Sahoo Swapan , Bowman Andrew , Sternai Pietro
Published: February 2023

We present evidence of a ca 200 m-thick Paleocene–Eocene Thermal Maximum (PETM) sedimentary section within a 543 m-thick deep-marine core in the Gulf of Mexico (GoM). The negative carbon isotope excursion (CIE) characteristic of the PETM is identified thanks to organic carbon stable isotopes and tightly linked to the Paleocene-Eocene boundary thanks to high-resolution biostratigraphic constraints provided by nannofossil and palynomorph assemblages. The unusual thickness of the CIE suggests that the PETM climate perturbation in the upstream North American catchments induced a substantial response in the downstream sectors of the Gulf Coastal Plain, and ultimately in the GoM. This relationship is illustrated in the deep-water basin by 1) the deposition of a shale interval when coarse-grained terrigenous material was trapped upstream at the onset of the PETM, and 2) considerable sediment supply in response to increased sediment transport upstream. These results are particularly relevant for paleoclimate and source-to-sink reconstructions because they link deep water sedimentation with a continental-scale paleo-drainage.
airSUM - Structure from Motion supported Stock Unearthing Method: Erosion modeling in Viennese vineyards
Authors: Kanta Robert , Kraushaar Sabine
Published: February 2023

Soil mobilization is particularly high in viticulture. In Austria and especially in Vienna, soil protection measures are frequently implemented, without the vintners knowing about the extent of erosion rates and where they can take additional measures in particular. However, new methods for erosion estimation with high accuracy and cost efficiency are expected to improve this situation. Of which one application will be presented in this study.A relatively fast and low-cost possibility is the stock unearthing method (SUM), which provides a rough estimation of erosion, based on biomarkers but neglects the inter-row area. The improved ISUM is using additional measurement points in this area and therefore delivering more accurate erosion volumes. Additionally, the use of structure from motion (SfM) DEMs provided respectable results on small plots in vineyards. The combination of SUM and SfM allows the new airSUM approach to provide a significantly more precise estimation of annual erosion rates, making rendering interpolation techniques unnecessary. The resulting model represents the present relief and is able to reproduce visible runoff patterns. The use of airSUM enabled the detection of 32.7 m3 (avg. of ~83.9 t ha-1 yr-1) soil erosion on an area of 700 m2 in a period of 8 years. Erosion hotspots could be modeled mainly in the wheel tracks with depths of up to 20.5 cm parallel to the slope and correspond excellently with field observations. This is partly due to the compaction of the surface, but mainly due to the preferential runoff and erosion. The identification of the erosion hot spots, runoff breaches and consequently runoff concentration allows the precise allocation of mitigation funds to reduce overland flow and erosion.
River water quality under climate change and extremes: a synthesis of impacts for river basins globally (Invited)
Authors: van Vliet Michelle T.H.
Published: February 2023

Long-term climate change and increased frequency and intensity of hydroclimatic extremes (e.g. droughts, heatwaves, floods) pose serious challenges for water management, not only in terms of water quantity, but also for securing suitable water quality for human use and ecosystems. Recent droughts, heatwaves and floods have been illustrative in showing major challenges due to exceeded water quality thresholds for sectoral use (e.g. inlet stops for drinking water production, irrigation). However, compared to water quantity, a limited number of studies have focused on water quality impacts, which are prevalent in many river basins of the world.This presentation provides a synthesis of the potential impacts of climate change and extremes (droughts, heatwaves and floods) on global river water quality considering various water quality constituents relevant for different sectoral uses and ecosystems. This synthesis is based on: 1) an extensive literature review of local, regional to global river water quality studies; 2) statistical analyses of water quality monitoring data in various river basins over the last 40 years; and 3) global river water quality projections generated by process-based global water quality models forced with bias-corrected climate change scenarios. Comparison of results over various river basins show overall consistent responses for some general water quality constituents (e.g. water temperature, dissolved oxygen, salinity) due to the predominance of generic mechanisms (e.g. lower dissolved oxygen solubility under warming). However, mixed responses are overall found for nutrients, pathogens and pharmaceuticals due to different counterbalancing mechanisms. In addition, water quality responses vary due to differences in constituent forms (e.g. dissolved vs. particulate nutrient forms) and persistence in surface waters (e.g. for pharmaceuticals). Furthermore, geographic, environmental and socio-economic (e.g. pollution management and infrastructure) conditions conspire, showing substantial impacts on the magnitude of water quality responses under climatic change and extreme events.
Adaptation of an experimental alluvial fan to climate change
Authors: Metivier Francois , Devauchelle Olivier , Delorme Pauline
Published: February 2023

We study the effect of an increase in flow discharge on the shape and growth of an experimental alluvial fan. The fan is built by a single-thread channel in which the flow occurs near the threshold of sediment motion. We first define a criterion that predicts the conditions under which a change in discharge leaves an inprint on the morphology of a fan. We then report on experimental runs which allow us to establish the relevance of this criterion. Experiments are carried out during which climatic changes are applied to the feeding channel of a fan. By playing on the initiation time of climate change, on the duration of the rise in flow, or on the total variation in discharge, we scan a range of configurations that allow us to qualitatively and quantitatively test our incision criterion. Qualitatively, we note that the dynamics of the fan seems altered only for values of the criterion which exceed the critical value of 1.5. In these situations, the channel stops moving and entranches. Quantitatively, we extract a characteristic time by autocorrelating spatio-temporal channel migration diagrams and show that this time correlates with the value of the incision criterion.
A model-based exploration of mid-Holocene anti-phase climate variations in the Central Andes
Authors: Sedhu-Madhavan Ardhra , G. Mutz Sebastian , Boateng Daniel , A. Ehlers Todd
Published: February 2023

The Andes’ elevation of ~4 km and great meridional extent of ~50°S to 10°N greatly influences the spatial climate patterns across the South American continent. Apart from latitude and altitude, quasi-stable pressure systems modify the climate of the region. The Bolivian high, an upper-level anticyclonic circulation over the central part of the continent, is one such feature and has a strong impact on atmospheric moisture transport and the regional hydroclimate of the Central Andes. Orbitally forced shifts in the Bolivian High have been hypothesised to be responsible for anti-phase palaeoclimate changes in Peru in the mid-Holocene, such as the increase in humidity in the Palpa region and synchronous extreme drought near Lake Titicaca [e.g., Mächtle et al. 2013]. However, this hypothesis has not been tested, and it has not been determined how much of the mid-Holocene hydroclimate change in the Central Andes can be explained by changes in regional pressure systems. Here, we test the hypothesis that mid-Holocene orbital variations and palaeogeographical changes modified pressure fields and regional moisture transport, and lead to anti-phase changes in regional hydroclimate. We test this hypothesis using the physics-based, isotope-tracking climate model ECHAM5-wiso. More specifically, we analyse pre-industrial and mid-Holocene paleoclimate simulations [Mutz et al. 2018]  to track changes in pressure fields and moisture transport. We then assess their impacts on regional hydroclimate in the Central Andes. Results indicate that: (a) the climate models reproduce the observed synchronous anti-phase (wetter and drier) climate changes documented in different parts of Peru, and (b) these can be explained by changes in the regional pressure and wind fields. Taken together, previous proxy-based observations and model results present here indicate that orbital variations drive changes in the regional pressure systems and lead to spatially heterogenous variations in hydroclimate across the Central Andes.
Quantifying surface cloud warming increase as Fall Arctic sea ice cover decreases
Authors: Arouf Assia , Chepfer Hélène , Kay Jennifer E. , L’Ecuyer Tristan S. , Lac Jean
Published: February 2023

During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low-level opaque clouds will increase surface cloud warming and could potentially delay sea ice formation. While more clouds due to fall sea ice loss have been observed, quantifying the surface warming caused by these cloud increases is observationally challenging. Here, we quantify surface cloud warming using spaceborne lidar observations. By instantaneously co-locating surface cloud warming and sea ice observations in regions where sea ice varies, we find October large surface cloud warming values (> 80 W m −2) are much more frequent (~+50%) over open water than over sea ice. Notably, in November large surface cloud warming values (> 80 W m −2) occur more frequently (∼+200%) over open water than over sea ice. These results suggest more surface warming caused by low-level opaque clouds in the future as open water persists later into the fall.
Reconstruct karst spring discharge data with hybrid deep learning models and ensemble empirical mode decomposition method
Authors: Zhou Renjie , Zhang Yanyan
Published: February 2023

Having a continuous and complete karst discharge data record is necessary to understand hydrological behaviors of the karst aquifer and manage karst water resources. However, caused by many problems such as equipment errors and failure of observation, lots of hydrological and research dataset contains missing spring discharge values, which becomes a main barrier for further environmental and hydrological modeling and studies. In this work, a novel approach that integrates deep learning algorithms and ensemble empirical mode decomposition (EEMD) is developed to reconstruct missing karst spring discharge values with the local precipitation. EEMD is firstly employed to decompose the precipitation data, extract useful features, and remove noises. The decomposed precipitation components are then fed as input data to various deep learning models for performance comparison, including convolutional neural network (CNN), long short-term memory (LSTM), and hybrid CNN-LSTM models to reconstruct the missing discharge values. Root mean squared error (RMSE) and Nash–Sutcliffe efficiency coefficient (NSE), are calculated to evaluate the reconstruction performance as metrics. The models are validated with the spring discharge and precipitation data collected at Barton Spring in Texas. The reconstruction performance of various deep learning models with and without EEMD are compared and evaluated. The main conclusions can be summarized as: 1) by using EEMD, the integrated deep models significantly improve reconstruction performance and outperform the simple deep models; 2) among three integrated models, the LSTM-EEMD model obtains the best reconstruction results among three deep learning algorithms; 3) For models with monthly data, the reconstruction performance decreases greatly with the increase of missing rate: the best reconstruction results are obtained when the missing rate is low. If the missing rate was 50%, the reconstruction results become notably poorer. For models with daily data, the reconstruction performance is less impacted by the missing rate and the models can obtain satisfactory reconstruction results when missing rates range from 10% to 50%.
Geomorphic Effects of Floods – Integrating Ancient, Modern and Experimental Data
Authors: Plink-Bjorklund Piret , Hansford Mark , Li Haipeng , Ono Kenya
Published: February 2023

Extreme river floods are among Earth’s most common and most destructive natural hazards and thus have a high impact on society. Their impact on shaping the landscapes and the sedimentary record is, however, less clear. The most common assumption is that moderate flood events build the sedimentary record, because (1) the high frequency moderate events are suggested to be more common and thus do more geomorphic work, (2) river recovery feedback loops are suggested to be negative and thus high-magnitude event effects are reworked, and (3) river sedimentary records are assumed to consist of ripple, dune and bar scale cross strata that indicate normal Froude subcritical flow, bedload transport, and equilibrium conditions for downstream bedform migration. However, there is a large and growing body of work that documents river deposits that are dominated by preserved high-magnitude flood deposits that consist of stacked flood event beds rather than equilibrium bedform strata, and indicate formative Froude supercritical flow conditions with suspension transport of sand and gravel.Based on a synthesis of ancient and modern river records, modern river discharge records and experimental data, we propose that there are fundamental differences in magnitude-frequency relationships and relaxation times in rivers with distinct hydrology, such that in some rivers channel recovery may be virtually non-existent and larger floods may leave permanent and formative imprints on landscape. Only if the ratio of the mean relaxation time (normal conditions) to the mean recurrence interval of extreme channel disturbing events is <1, and the critical shear stress for sediment motion is exceeded during moderate (normal) conditions can a river recover from extreme flood-induced change before the next major disturbance occurs. This concept helps to explain the observed variability in the sedimentary record of rivers, as well as critical differences in river flood hazards.
Compaction localization in 4D imaged by X-ray Computed Tomography and Digital Volume Correlation
Authors: Baud Patrick , Meng Fanbao , Huang Lingcao , Wong Teng-fong
Published: February 2023

Understanding compaction localization in porous limestone in the laboratory is significantly more challenging than in sandstone because of the lack of consistent acoustic emission activity in carbonate samples. Previous studied have therefore relied on X-ray Computed Tomography imaging (CT). The first unambiguous evidence of compaction band development in limestone was provided by Huang et al. (2019), who performed synchrotron in situ CT imaging during shear-enhanced compaction in a sample of Leitha limestone. This sample was deformed in the HADES rig at the European Synchrotron Radiation Facility, in dry conditions and at a confining pressure of 20 MPa. In this study, we analysed this data set using Digital Volume Correlation (DVC). Not only could we use DVC to characterize quantitatively the spatiotemporal development of displacement and strain, we were also able to compare with direct observations to assess the stress-induced damage in multiple scales. Our new results confirm that inelastic compaction occurred in two stages in Leitha limestone: macropore collapse first and then sequential growth of compaction bands. In the pore collapse stage, DVC reveals complex and heterogeneous grain-scale strains, implying significant heterogeneity in the internal stress field. Such complexity is to be accounted for if one were to connect micromechanical and continuum models. At higher stresses, we have obtained further quantitative constraints on the spatial distribution of volumetric and shear strain during the growth of compaction bands. Our results demonstrate that compaction banding in Leitha limestone can be analysed as a bifurcation phenomenon, that would typically occur preferentially in zones of high porosity. The displacement field inferred from DVC revealed that the bands showed mostly normal displacement discontinuities, as expected for compaction bands. DVC analysis also gave more constraints on band geometric attributes. Analysis of the autocorrelation function for the strain suggested that the decay and rebound of the autocorrelation as a function of the axial separation may provide proxies for the mean width and spacing of compaction bands. The 2D autocorrelation function on the band planes also provides relevant clues on the complex sequential growths of the compaction bands.
Hydrological Drivers for the Spatial Distribution of Wetland Herbaceous Communities in Poyang Lake
Authors: Huang Wenqin , Hu Tengfei , Mao Jingqiao , Montzka Carsten , Bol Roland , Wan Songxian , Li Jianxin , Yue Jin , Dai Huichao
Published: February 2023

Hydrological processes are known as major driving forces in structuring wetland plant communities, but the specific relationships are not always well understood. The recent dry conditions of Poyang Lake (i.e., the largest freshwater lake in China) are having a profound impact on its wetland vegetation, leading to the degradation of the entire wetland ecosystem. We developed an integrated framework to quantitatively investigate the relationship between the spatial distribution of major wetland herbaceous communities and the hydrological regimes of Poyang Lake. First, the wetland herbaceous community classification was built using a support-vector machine and simultaneous parameter optimization, achieving an overall accuracy of over 98%. Secondly, based on the inundation conditions since 2000, four hydrological drivers of the spatial distribution of these communities were evaluated by canonical correspondence analysis. Finally, the hydrological niches of the communities were quantified by Gaussian regression and quantile methods. The results show that there were significant interspecific differences in terms of the hydrological niche. For example, Carex cinerascens Ass was the most adaptable to inundation, while Triarrhena lutarioriparia + Phragmites australis Ass was the least. Our integrated analytical framework can contribute to hydrological management to better maintain the wetland plant community structure in the Poyang Lake area.
Improving STEM Education Across European Schools
Authors: Grozavescu Nadia
Published: February 2023

My name is Nadia Grozavescu and I am a teacher at Gheorghe Magheru Secondary School in Caracal, Romania. I would like to present you the following project, entitled “Improving STEM Education Across European Schools” (Erasmus+ KA201). The project took place in the school I teach between 2020 and 2022.The overall goal of the project was developing a methodology for teachers to deliver innovative teaching styles to make the STEM evaluation more efficient and its implementation more attractive for students.Over the course of the project we obtained the following results:10 STEM pedagogical scenarios of which two were created by the teachers in our school. These were also translated in Romanian and listed on the project website (https://improving-stem-education.eu/teaching-materials/). I have personally contributed to the one about the active engagement in respecting the habitat.
25 online courses, grouped on nine STEM themes, of which five were created by our school’s coordinator. Again, all courses were translated and can be found on the project’s webpage (https://e-learning.improving-stem-education.eu/)
30 students' mentoring sessions, of which six were hosted by Romanian mentors who answered our call. The sessions were recorded and can be found here https://improving-stem-education.eu/mentoring-scheme/
Three learning and teaching training mobilities which ten of our school’s teachers benefited of. These took place in Greece (Nov 2021), Belgium (Apr 2022) and Ireland (Jun 2022) and had the following main themes: Class Management, Students Motivation, Robotics and Programming, 3D printing and Laser cutting. I was one of the teachers who took part in the workshop in Belgium
The project proved to be complex and challenging, even more given the fact that we were the only institution dealing with younger students. Over the project our school partnered with a university, a Science House Centre, a centre for teachers’ professional development, an IT company, and an NGO dedicated to improving teaching.
Citizen science observations capture global patterns of plant traits
Authors: Wolf Sophie , Mahecha Miguel , Sabatini Francesco Maria , Wirth Christian , Bruelheide Helge , Kattge Jens , Moreno Martínez Álvaro , Mora Karin , Kattenborn Teja
Published: February 2023

As global change accelerates, the urgency for a solid understanding of biosphere-environment interactions grows. However, we need more data on plant functional traits to test such relationships reliably across ecosystems. The TRY database contains an impressive collection of plant trait measurements for thousands of species already, and there have been some approaches to spatially extrapolate them using geospatial predictors and remote sensing data; however, the original data is spatially sparse so that extrapolations come with substantial uncertainties. At the same time, citizen scientists have collected increasingly dense observations of species occurrences around the globe. Here, we test if we can link species occurrences from the citizen science project iNaturalist with trait observations from TRY to produce global trait maps without the need for spatial extrapolation. We generated spatial grids for 18 traits, calculating a mean for each grid cell by averaging trait values associated with observations within that cell. We compared mean trait values from iNaturalist observations to community-weighted mean traits from sPlotOpen, a globally sampled dataset of vegetation plot data. Our results show correlations between the two datasets of up to r = 0.69, especially in biomes with higher iNaturalist observation density and those not dominated by trees. Also, we show that iNaturalist-derived maps have higher correlations to sPlotOpen-derived maps than previously published trait maps. This strong correlation between two fundamentally different datasets is astounding and unexpected. iNaturalist is noisy and heterogenous, sampled by citizen scientists who share the species they encounter and find interesting; sPlotOpen is a data collection of vegetation plots that were measured and recorded within the framework of specific research questions. The fact that these two datasets exhibit such a strong resemblance opens up a promising avenue for using the data treasure trove that is crowd-sourced data to help fill the gaps in plant trait data and demonstrates that crowd-sourced data, such as the iNaturalist observations, can be used to complement professional data collection efforts.