bluuebunny/crossref_metadata_2025 huggingface dataset:
Low flow sensitivity in central and southwestern Europe to water withdrawals under 2K global warming
Authors: Greve Peter , Burek Peter , Guillaumot Luca , van Meijgaard Erik , Aalbers Emma Elizabeth , Smilovic Mikhail , Sperna-Weiland Frederiek , Kahil Taher , Wada Yoshihide
Published: February 2023

A sufficient freshwater supply is vital for humans, ecosystems, and economies, but anticipated climate and socio-economic change are expected to substantially alter water availability. Across Europe, about 2/3 of the abstracted freshwater comes from rivers and streams. Various hydrological studies address the resulting need for projections on changes in river discharge. However, those assessments rarely account for the impact of various water withdrawal scenarios during low flow periods. We present here a novel, high-resolution hydrological modeling experiment using pseudo-global warming climate data to investigate the effects of changing water withdrawals under 2K global warming. We find substantial sensitivities in projected low flows to varying water withdrawal assumptions, especially across Western and Central Europe. Our results highlight the importance of accounting for future water withdrawals in low flow projections, showing that climate-focused impact assessments in near-natural catchments provide only one piece of the anticipated response and do not necessarily reflect changes in heavily managed river basins.
Simulating the success of plant hydraulic strategies within a global vegetation model
Authors: Pugh Thomas A. M. , Eckes-Shephard Annemarie , Liu Daijun , Esquivel-Muelbert Adriane , Matthews Thomas , Papastefanou Phillip , Rammig Anja , Sadler Jonathan
Published: February 2023

Today’s forest carbon stocks are threatened by climate change through many types of disturbances, including drought. State-of-the-art Dynamic Global Vegetation Models (DGVMs) have hitherto not been able to explicitly simulate the response of tree hydraulic systems to drought, which are ultimately important determinants of tree resilience during drought events. Increasingly, more detailed representations of plant hydraulics, including death by cavitation, are being included in DGVMs, but simulations at the global level have been challenging, partially due to the lack of data for parameterisation. To overcome these issues, we compiled a large dataset of hydraulics-relevant plant traits from the literature (including TRY). To overcome the sparseness of the available trait data, we used literature on the functional relationships between traits to create a hypothesis framework that functionally links multiple traits and their trade-offs together in a network. From this network of traits we can sample parameter sets that reflect coherent plant strategies. We applied these strategies in the plant-hydraulics-enabled DGVM LPJ-GUESS and show how they can be used to provide model-based hypotheses of how both strategies and individual trait values vary across different forest environments. These results provide a basis for global-scale hydraulic model parameterisation, as well as providing verifiable hypotheses for testing in the field. 
Estimating subsoil diffusivity and respiration by inverse modelling: results from first case studies
Authors: Maier Martin , Osterholt Laurin , Jochheim Hubert , Schack-Kirchner Helmer
Published: February 2023

Soils are important terrestrial biological reactors and play a central role in the global carbon (C) and nitrogen (N ) cycle. Soils can store large amounts of C and N, but they also can be a major source (or sink) of greenhouse gases. The highest C and N concentrations are usually found in the topsoil, which is also the biologically most active soil layer, and the origin of most soil respiration. Subsoil (>0.5m depth) usually has lower C and N contents, and the contribution to the soil surface gas fluxes, e.g. soil respiration is low. Nevertheless, the total amount of C and N stored in the subsoil (e.g. 0.5-3m) can be large. Slow changes due to global climate change (e.g. in subsoil moisture or temperature) might affect subsoil respiration, i.e. subsoil C mineralization, and thus, might have a substantial long-term effect on subsoil C and N storage.While gas fluxes from soil surfaces are usually measured by chamber methods or the Eddy-covariance method, these methods are not suitable to assess subsoil gas fluxes. The gradient method allows calculation of gas fluxes in a soil profile, that means also in the subsoil, based on a measured soil gas profile and a known soil gas diffusivity (Maier & Schack-Kirchner, 2014). Estimating the latter is a major challenge, especially in subsoils, and the (unreflective) application of a general soil gas diffusivity model without prior knowledge of the soil physical characteristics of the subsoil can result in large uncertainties.We present soil CO2 data from a deep soil profile (1m) of a forest site (Jochheim et al., 2022) from which we chose special and typical situations of daily CO2 cycles at different soil depths. We used time-dependent Finite Element Modelling (COMSOL) to run different scenarios to investigate the phase shift and damping of diurnal CO2 cycles in the atmosphere/topsoil and subsoil, which allows to derive soil gas diffusivity of the subsoil. We tested the susceptibility of the approach to misinterpretation due to possible inaccurate assumptions by further scenarios. To evaluate the effect on the derived subsoil gas flux, we will use diffusivity values from this new in situ approach and known general soil gas diffusion models as well.
The Signature of Snow Drought: A Spatially-Connected Approach to Understanding Forest Water Stress
Authors: Graup Louis , Tague Naomi
Published: February 2023

Globally, and especially in Mediterranean-type ecosystems (MTEs), forests are increasingly vulnerable to drought stress, leading to high rates of mortality. Global climate models project increased drought frequency and severity, with higher temperatures leading to snow droughts. Warm snow droughts are produced by warming temperatures that prevent precipitation from accumulating on the landscape as a snowpack. Dry snow droughts have very little rain or snow. Any drought reduces water availability and increases vegetation water stress. But in the complex topography of mountain environments, spatial patterns of drought stress and subsequent tree mortality are influenced by snowmelt and subsurface lateral redistribution. Along a hillslope, snowmelt induces hydrologic connectivity, enhancing groundwater recharge and lateral flows. Riparian vegetation benefits from these upslope subsidies, which makes riparian trees more productive but also more sensitive to climate variability. This research seeks to understand, what is the implication of snow drought for hillslope ecohydrology? Using observed sap flow data taken along a topographic gradient in an experimental watershed in the Sierra Nevada, CA, we calibrate an ecohydrological model (RHESSys) to consider the effects of climate, geology, and forest management on riparian water stress. We demonstrate that riparian trees are buffered against drought stress by lateral inputs at our groundwater-dominated study site. But riparian forests without a significant groundwater influence will not be so fortunate. I am proposing an international collaboration between US and EU ecohydrologists to understand the conditions that lead to greater riparian water stress in Mediterranean ecosystems and determine potential solutions to protect these sensitive hydrological microrefugia.
Global microplastic emission and deposition fluxes at the ocean-atmosphere interface
Authors: Bucci Silvia , Richon Camille , Bakels Lucie , Stohl Andreas
Published: February 2023

While microplastics (MP) have been recently identified and recognized as a pollutant for the atmospheric environment, little is known about their actual emissions and concentration in the atmosphere. In this work, we follow a bottom-up approach to estimate the fluxes of MP at the ocean-atmosphere interface.Coupling a sea spray emission scheme (Grythe et al. 2014) with the MP concentrations over the ocean surface simulated by the NEMO-PISCES general circulation model (Nucleus for European Modelling of the Ocean, Pelagic Interaction Scheme for Carbon and Ecosystem Studies, Richon et al. 2022), we estimate the global sea spray MP emissions at 6-hourly resolution, over a one-year period.The MP emission fluxes are then fed into the Lagrangian atmospheric dispersion model FLEXPART (Stohl et al., 2005; Pisso et al., 2019), driven with hourly ERA5 data at 0.5° horizontal resolution, to provide a global picture of the atmospheric cycle of the MP of marine origin.We discuss the main emission areas and their marked seasonal variability, the resulting atmospheric concentration across the globe and the deposition fluxes on both land and ocean surfaces. Finally, we compare simulated fluxes and concentrations with existing observations of MP in the marine atmosphere.
Storm Surge and Sea Level Rise Effect Assessment Over Istanbul Downtown Transportation Network
Authors: Zengin Enes
Published: February 2023

It is expected that with the increased carbon emission rates around the world impact of global warming will become more severe every year. There are extreme variations in the extent of natural events, such as temperature changes, amount of precipitation, and storm strength. Today, more than 3 billion people live within 200 kilometres inland from the coastline, about half of the world's population. Considering today's cities and population distributions, ongoing research focuses on to what extent they are prepared for these climatic changes and their effects. Especially in megacities close to the shore like Istanbul, buildings, roads, and public transportation networks on the coastline can be damaged due to storm surges and sea level rise from time to time, even in short-term heavy rains. Effect of storm surges and sea level rise effect over mega cities' coastal areas having low-lying topographies have a risk of creating destructive effects. A considerable part of the population of Istanbul, the 1st in Europe and the 14th in the world, with its population approaching 16 million, lives on the shores of the Marmara and Bosphorus. It is crucial for Istanbul, a polycentric city spread over two continents, Asia, and Europe, that the transfer hubs and transportation network provide 24-hour uninterrupted service. However, some metro, tram, ferry, and bus transfer hubs and important stations are only a short distance from the coastline. For this reason, it is essential to determine the hubs and stations at risk in the transportation network, considering storm surges and sea level rise scenarios, considering the disasters experienced in the past. Therefore, the digital elevation maps with 25 meters resolution provided by Copernicus Land Monitoring Service were used to create two scenarios for storm surges and sea level rise to assess the inundation risk of Istanbul's transportation networks close to the coastline. It has been revealed that the transportation network elements located in Kadıköy, Harem and Üsküdar on the Anatolian Side and Beşiktaş, Kabataş, Karaköy and Eminönü on the European Side are at serious risk. As a result of any disaster that may occur in these regions, problems that may cause problems will occur throughout Istanbul and disrupt public transport temporarily. It is planned to prepare more detailed storm surge and sea level rise maps by using high-resolution digital elevation models based on location to define risk in more detail. This way, a practical research output can be provided for research partners and public authorities to develop policies and mitigation strategies for transportation network interruption against storm surges and sea level rise.
Vadose zone water content characterization of a heterogeneous limestone by 3D-SNMR
Authors: Ryckebusch Clémence , Baltassat Jean-Michel , Legchenko Anatoly , Kessouri Pauline , Amraoui Nadia , Abbas Mohamad , Azaroual Mohamed
Published: February 2023

In the current climate change context, the quality and availability of water resource are important society issues. Indeed, the consumption of water and fertilizers by farms and their discharge into the soil and aquifers leads to a critical environmental situation. To manage the effect and fate of these contaminations, it is necessary to have a relevant knowledge of the vadose zone dynamics and exchanges especially flow paths from the soil to the deep aquifers. Parts of the vadose zone are well studied such as the first meters with an adapted instrumentation, and the water table properties with piezometric measurements and pumping tests. The geophysics methods allow studying the deep vadose zone properties. The surface nuclear magnetic resonance (SNMR) is a direct geophysical method based on the protons magnetic resonance to measure water content in the subsurface. This method can be used to detect the water table level coupled with hydrogeological measurements (piezometric measurements and pumping tests) or to characterize aquifers properties and boundaries coupled with other geophysical methods (electrical, EM or gravimetric methods). The current study is carried out in Villamblain (France) at the heart of the Beauce region; one of the most cultivated and highly nitrate-contaminated area in France. The vadose zone is a highly heterogeneous limestone with geochemical alteration, complex network of fractures and karstification. This field site was chosen to develop an observatory of transfers in the Vadose Zone named O-ZNS (https://plateformes-pivots.eu/o-zns/). This observatory consists of an exceptional well (20 m-deep and 4 m-diameter) equipped with multiple sensors and accessible for direct characterization of the heterogeneous vadose zone, surrounded by 8 boreholes used for water sampling, geophysical well-logging, piezometric level monitoring and vadose zone geochemical properties monitoring.    In this study, the SNMR method is used (1) to characterize the spatial heterogeneities of the 3D aquifer and of the vadose zone limestone, in a 3D-model jointly interpreted with other geophysical measurements (3D-ERT, 3D-IP, gravimetric, GPR profiles) and soundings; (2) to characterize the vadose zone water content, in combination with GPR and NMR logging water content profiles. Both these works are ongoing.   This research aims to know more accurately the vadose zone water content measured by SNMR in the context of a heterogeneous limestone with the goal to monitor the vadose zone flow dynamics with time-lapse measurements coupled with hydrogeological measurements.   
Quantile regression of satellite-derived CDOM for river plume dispersion in southern Hudson Bay
Authors: Basu Atreya , McCullough Greg , Bélanger Simon , Doxaran David , Sydor Kevin , Barber David
Published: February 2023

Physical and biogeochemical processes in coastal waters are shaped by salinity variation induced by river water mixing. As salinity is intrinsic to any aquatic ecosystem, any change will challenge the ecological framework. Thus, space-based monitoring of salinity in regions susceptible to salinity changes, such as estuaries and nearshore waters, is the need of the moment and supports Sustainable Development Goal 14 of the United Nations. Therefore, the salinity monitoring process addresses salinization/de-salinization issues of transitional waters. Current sea surface salinity products from satellites, such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), exclude shallow waters, creating a salinity data gap in the land-ocean continuum. Such a gap in salinity considerably prevents continuous and synoptic river plume monitoring using satellite observations. Light absorption properties were studied in the coastal waters of Hudson Bay and James Bay, the shallow inland seas of Canada, to overcome the problem. River water carries terrestrial signals into the estuarine and coastal seas through dissolved organic matter (DOM) and inorganic sediments. DOM and sediments in seawater interact with the visible spectrum of solar radiation that can be mapped using ocean color remote sensing. Colored dissolved organic matter (CDOM), the optically active portion of DOM, dominates the light absorption budget at 412 nm in the coastal waters of Hudson Bay and James Bay, followed by the suspended inorganic solids. Hudson Bay waters were clearer relative to James Bay, with a higher content of river-sourced CDOM. The concentration of these river-derived optical tracers decayed offshore. CDOM underwent conservative dilution with increasing salinity, while suspended sediments were non-conservative. Therefore, based on the conservative CDOM and salinity relationship, a quantile regression approach was developed to quantify the Nelson River water dispersion in Hudson Bay using CDOM concentrations retrieved from moderate resolution imaging spectroradiometer (MODIS) images. This novel method permits the mapping of surface river water mixing with sea waters in terms of the distance from the river mouth corresponding to different percentages of diluted river water and the direction of river water transport. Such a strategy assists in coastal management, such as identifying the marine conservation area's geographic boundaries and conducting water quality tests to assess the health of coastal waters.
Neural-network-based super-resolution on unstructured meshes of coastal spectral wave computations
Authors: Kuehn Jannik , Abadie Stéphane , Roeber Volker
Published: February 2023

High-resolution wave forecasts are of critical importance for coastal safety, hazard prevention, and energy transition. Examples that benefit from detailed information of coastal sea states range from the adaptation of coastal protection to beach goer and marine safety and even include the growing market of marine renewable energy. While regional and global wave forecasts exist, local high-resolution details are often not accessible due to the associated computational cost.In our work we use a neural network to apply a so-called super-resolution approach that can turn wave forecasts computed over coarse grids into substantially higher resolution at very low computation cost and with only little loss of overall quality. The idea is to train the neural network with pairs of coarse and fine-grid computations, so that later on wave computations over coarse grids can be converted into a higher resolution. While the amount of saved computation time varies with the level of resolution between coarse and fine grid, the super-resolution approach can be more than 50-times faster than a direct high-resolution computation and still provide good accuracy.Here we will present a case study on a 44-year hindcast of the French Basque coast, with which we trained and tested multiple networks. We will comment on the dependency of model performance on the amount of training data and the difficulties of an unstructured grid, compared to a structured one. More specifically, structured grids can be handled as regular images, which makes the adaptation of classical and powerful convolutional neural networks to the problem relatively easy. The application to irregular grids, however, is not trivial and requires different approaches like graph neural networks or multi-layer perceptrons.  Lastly, we will compare the performance of a surrogate model, that is, a neural network that simply replaces completely a spectral wave model like SWAN, with our super-resolution approach, that uses coarse wave model computations as an input. We argue that both approaches are complementary and have their advantages and disadvantages in specific settings. 
Detection of local atmospheric methane enhancements by analyzing Sentinel-5 Precursor satellite data
Authors: Vanselow Steffen , Schneising-Weigel Oliver , Buchwitz Michael , Bovensmann Heinrich , Burrows John P.
Published: February 2023

Methane CH4 is an important anthropogenic greenhouse gas and its rising concentration in the atmosphere contributes significantly to global warming. Satellite measurements of the column-averaged dry-air mole fraction of atmospheric methane, denoted as XCH4, can be used to provide information about the location of methane sources and on their emissions, which can help to improve emission inventories and review policies to mitigate climate change.   The Sentinel-5 Precursor (S5P) satellite with the TROPOspheric Monitoring Instrument (TROPOMI) onboard was launched in October 2017 into a sun-synchronous orbit with an equator crossing time of 13:30. TROPOMI measures reflected solar radiation in different wavelength bands to generate various data products and combines daily global coverage with high spatial resolution. TROPOMI's observations in the shortwave infrared (SWIR) spectral range yield methane with a horizontal resolution of typically 5.5 x 7 km2. We used a monthly XCH4 data set (2018-2021) generated with the WFM-DOAS retrieval algorithm, developed at the University of Bremen, to detect regions with temporally persistent, locally enhanced XCH4. At first, we applied a spatial high-pass filter to the XCH4 data set to filter out the large-scale methane fluctuations. The resulting anomaly ΔXCH4 maps show the difference of the local XCH4 values compared to its surroundings. We then analyzed the monthly anomaly maps to identify potential source regions with persistent XCH4 enhancements by utilizing different filter criteria, such as the number of months in which the local methane anomalies ΔXCH4 must exceed certain threshold values. As a next step, we used a simple mass balance method to estimate the monthly emissions and the corresponding uncertainties of the detected potential source regions from the monthly averaged XCH4 maps. In the last step, we interpreted the emissions of the potential source regions in terms of the source type, by comparing the detected potential source regions with emission databases based on a spatial analysis. In this presentation, the algorithm and initial results concerning the detection of regions with temporally persistent, local XCH4 enhancements, originating from localized potential methane sources (e.g., wetlands, coal mining areas, oil and gas fields) are presented.     
Technical Performance Assessment of the Subak Heritage Irrigation System in Bali, Indonesia
Authors: Mawardhi Andre Dani , Linga Seth Nathaniel
Published: February 2023

Subak is a socio-agrarian-religious system of integrated terrace irrigation management on Bali island that involves indigenous peoples and religious aspects in distributing water sources evenly to rice fields. Regardless of its heritage value, Subak irrigation's performance in distributing water for rice is necessary in terms of water scarcity and food production issues. However, there is a limited number of works evaluating the Subak irrigation system's functioning, although it has been present for centuries. This study was conducted to assess the performance of Subak Ulumayu and Subak Sembung in 2018/2019. Several spatial datasets were processed using pySEBAL to generate biomass, evapotranspiration, and transpiration data. Results showed that rice consumed 968-1014 mm of water, which resulting 4.87-4.93 tons rice/ha in this season. Most subfields showed relatively good performance, i.e. Relatively Water Deficit <0.2, adequacy >80%, and equity CV<10%, although the Relatively Yield Deficit was high and efficiency was slightly low. According to those results, both Subak irrigation systems were working satisfactorily to supply water for rice fields among water users. However, there is a remained challenge to optimize rice productivity to contribute to national food security.
Simulating dryland cliffs evolution in response to extreme rainstorms
Authors: Shmilovitz Yuval , Rossi Matthew , Tucker Gregory , Campforts Benjamin , Pederson Joel , Morin Efrat , Armon Moshe , Enzel Yehouda , Haviv Itai
Published: February 2023

Cliff bands are common in drylands and their evolution is often influenced by hydrogeomorphic processes. It has been previously suggested that cliff retreat patterns and morphology are affected by the properties and frequency-magnitude relations of rainstorms. However, basic questions on this topic persist because landscape evolution models typically do not account for the surface processes like runoff generation and sediment transport that occur under short-duration (sub-hourly) intense rainfall. Here we test the hypothesis that changes in rainstorm properties can systematically alter cliff retreat patterns and morphology. We developed a novel numerical model that simulates the response of cliffs and associated sub-cliff slopes to various rainstorm regimes to (1) identify dominant cliff morphologies, and (2) examine if extreme rainstorm properties are encoded in the topography. The new model utilizes the Landlab modeling toolkit and includes an explicit novel representation of surface processes that occur during short-duration rainstorms, including cliff-weathering, infiltration, runoff generation, clast fragmentation, and size-dependent sediment transport. Using a suite of numerical experiments, we vary model parameters and rainfall types and simulate changes in cliff retreat patterns and morphology. Our model results agree well with analytical predictions for cliff morphology under a control case of no transport on the sub-cliff slope, indicating a good representation of processes. Furthermore, sensitivity analyses on cases where sediment transport is explicitly included show that cliff evolution is highly dependent on both the grain size of sediment derived from the cliff and the rainfall intensities. These two factors can alter retreat patterns and determine whether and how fast the cliff can be buried under its own sediment. Numerical experiments based on rainfall and field measurements from the central Negev desert (eastern Mediterranean) demonstrate that including the dynamics of high-intensity rainfall and sediment grain size can help explain observed topographic trends. In addition, for a given imposed storm depth, we find that the rainstorm intensities pattern strongly influences both the cliff retreat and its morphology. Short rainstorms with higher intensities are much more erosive than longer storms with lower intensities. This latter case frequently triggers cliff burying. Taken as a whole, our results demonstrate that cliff evolution and morphology are significantly affected by storm-scale sediment transport dynamics and thus highlight the importance of incorporating high-resolution rainfall forcing into landscape evolution models of dryland landforms.
Combined measurements with the EISCAT radar and the Nordic Meteor Radar Cluster to determine AGW-TID wave parameters
Authors: Günzkofer Florian , Pokhotelov Dimitry , Stober Gunter , Mann Ingrid , Vadas Sharon L. , Becker Erich , Tjulin Anders , Gulbrandsen Njål , Kero Johan , Kozlovsky Alexander , Lester Mark , Mitchell Nicholas , Nozawa Satonori , Tsutsumi Masaki , Borries Claudia
Published: February 2023

Atmospheric Gravity Waves (AGWs) forced in the lower atmosphere are known to have a significant impact on the mesosphere and lower thermosphere (MLT) region. In the ionosphere, they can generate Medium-Scale Traveling Ionospheric Disturbances (MSTIDs). These disturbances roughly occur on time scales of 15−80 min and are therefore often parametrized rather than directly resolved in ionosphere models. The energy and momentum transport by AGW-TIDs strongly depends on their wave parameters. Measurements of AGW-TIDs in the MLT region and determination of the wave parameters (vertical and horizontal wavelength, wave period and propagation direction) are therefore an essential step to improve ionosphere modelling. However, measurements that provide a good resolution in the vertical dimension (≲ 10 km) and time (≲ 10 min) as well as a large enough coverage in the horizontal dimension (≳ 300 × 300 km) are difficult at MLT altitudes. We show, that combined measurements of the EISCAT VHF incoherent scatter radar and the Nordic Meteor Radar Cluster allow to determine the wave parameters of AGW-TIDs across the whole MLT region. Fourier filter methods are used to separate wave modes by wavelength, period and propagation direction. The extracted wave modes are fitted with wave functions in time-altitude and horizontal cross sections which gives the wave parameters. The coverage regions of the two applied instruments are separated only by approximately 10 km in altitude, which allows to identify a single wave mode in both measurements. We present the developed techniques on the example of a strongly pronounced AGW-TID measured on July 7, 2020. As a first application, two measurement campaigns have been conducted in early September and mid-October 2022 to study possible changes in AGW-TID parameters due to the MLT fall transition occurring around equinox. Another possible application of our method is to infer thermospheric neutral winds from the observed waves. We demonstrate this process under the assumption of the anelastic dissipative gravity wave dispersion relation.
On the optimization of grand multi-model probabilistic performance and the independence of the contributing seasonal prediction systems
Authors: Alessandri Andrea , Catalano Franco , Nielsen Kristian , Troccoli Alberto
Published: February 2023

To optimize the performance of seasonal climate forecasts we used a Grand Multi-Model Ensemble (MME) approach. The Grand MME consists of five Seasonal Prediction Systems (SPSs) provided by the European Copernicus Climate Change Service (C3S) and of other six SPSs independently developed by centres outside Europe, five by the North American (NMME) plus the SPS by the Japan Meteorological Agency (JMA).All the possible Grand MME combinations have been evaluated for temperature and precipitation, for different geographical regions. Results show that, in general, only a limited number of SPSs is required to maximize the skill. Although the selection of models that optimize performance is usually different depending on the region, variable and season, it is shown that the performance of the Grand-MME seasonal predictions is enhanced with the increase of the independence of the contributing SPSs.Independence is measured by using  a novel metric developed here, named the Brier score covariance (BScov), which estimates the relative independence of the SPSs. Together with probabilistic skill metrics, BScov is used to develop a strategy for an effective identification of the combinations of SPSs that optimize the probabilistic performance of the predictions, thus avoiding the inefficient and ineffective use of all SPSs available.
Machine Learning-driven Infilling of precipitation recordings over Germany
Authors: Filippou Danai , Plésiat Étienne , Meuer Johannes , Thiemann Hannes , Ludwig Thomas , Kadow Christopher
Published: February 2023

Weather radars are a significant component of modern precipitation recordings,as they provide information with high spatial and temporal resolution. However, radars as a tool for weather applications emerged only after the 1950s. AI/ML methods have proven to be successful when it comes to determining patterns and connections between related fields in space and time. Moreover, AI/ML methods have exhibited remarkable skill in infilling missing climate information (see Kadow et al. 2020). Desired outcomes of the project include using these AI/ML techniques to build a spatial precipitation field by combining station and radar data. We will use data from two well-known datasets: RADOLAN and COSMO-REA2. The validity of this digital twin will be investigated by comparing its output with other reanalysis data (e.g. ERA5). Further evaluation can be carried out by testing the radar field’s accuracy in detecting extreme precipitation events in the past (e.g. heavy rain events in the summer of 2021 in Western Germany). We aim for the creation of a radar field that will be successfully projected in the past. Moreover, it will uncover new information on regional climatology, especially in areas where station data is sparse.
Hydrogen Escape Rates 2021-2023 Retrieved from Emirates Mars Mission Observations
Authors: Chaffin Michael , Deighan Justin , Jain Sonal , Holsclaw Greg , Susarla Raghuram , AlMazmi Hoor , Chirakkil Krishnaprasad , Correira John , England Scott , Eparvier Frank , Evans J. Scott , Fillingim Matt , Lillis Rob , Lootah Fatma , Thiemann Ed , Curry Shannon , AlMatroushi Hessa
Published: February 2023

The surface of the planet Mars exhibits a record of dessiccation and oxidation, the legacy of significant water escape to space as hydrogen and oxygen. This H escape can be constrained using ultraviolet observations of the planet's upper atmosphere, where neutral atomic hydrogen scatters UV sunlight. In the time since its orbit insertion in early 2021, the Emirates Mars Ultraviolet Spectrometer (EMUS) on the Emirates Mars Mission (EMM) has been observing this hydrogen at 102.6 nm and 121.6 nm, H Lyman beta and Lyman alpha. Here we present H escape rates retrieved from these observations, obtained using a 3D radiative transfer model that simulates the brightness of both spectral lines, combining their information content to constrain the atmospheric state. In agreement with past results, we find that H escape peaks around Southern Summer solstice, after perihelion, exhibiting a more than 10x increase relative to Northern Summer conditions. Importantly, our retrievals extract information about both the hydrogen density and temperature, and do not require independent assumptions about the upper atmosphere temperature. We will discuss prospects for extending these retrievals beyond the current EMM dataset as well as implications for the long-term evolution of the Mars atmosphere.
Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms
Authors: Laske Gabi , Frazer William , Doran Adrian
Published: February 2023

Surface wave arrival angles are an important secondary set of observables to constrain Earth's 3-dimensional structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single 3-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets where station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. In a previous paper, we demonstrated that our automated Python-based toolbox DLOPy compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides  individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009  that were recorded at the USArray Transportable Array (TA), a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented. While the proper choice of the start time of the analysis window may depend on a particular geographic location of a seismic network, our observations for USArray data suggest that a slightly later start time than is currently used may yield more high-quality Rayleigh wave measurements.
Orbital pacing of Southeast Atlantic carbonate deposition since the Oligocene (30-0 Ma): tracing entwined climate and carbon cycle interactions
Authors: Drury Anna Joy , Liebrand Diederik , Westerhold Thomas , Beddow Helen M. , De Vleeschouwer David , Hodell David A. , Rohlfs Nina , Wilkens Roy H. , Lyle Mitchell , Bell David B. , Kroon Dick , Pälike Heiko , Lourens Lucas J.
Published: February 2023

The last 30 million years (Myr) of Cenozoic climate change broadly charted the transformation from a world with solitary Antarctic ice sheets through to a bipolar glaciated Earth. Highly resolved records of carbonate content (%CaCO3) provide insight into regional impacts of ever shifting climate, cryosphere and carbon cycle interactions. Here, we use X-ray fluorescence (XRF) ln(Ca/Fe) data collected at Ocean Drilling Program Site 1264 (Angola Basin side of Walvis Ridge, SE Atlantic Ocean) to generate the first SE Atlantic %CaCO3 record spanning 30-0 Myr ago (Ma). Minimal changes in terrigenous-derived XRF data supports that the %CaCO3 reflects the balance between productivity and dissolution in this region. This XRF data also helped to formulate a comprehensive and continuous depth and age model for the entirety of Site 1264 (~316 m; 30-0 Ma). These verified depth and age models constitute a key framework for future palaeoceanographic studies at this location.We identify three phases with distinctly different orbital imprints of CaCO3 deposition in the SE Atlantic. The shifts between these phases broadly occur across major developments in climate, the cryosphere and/or the carbon cycle: 1) strong ~110 kyr eccentricity pacing prevails during Oligo-Miocene global warmth (~30-13 Ma); 2) eccentricity-modulated precession imprints more strongly after the mid Miocene Climate Transition (mMCT) (~14-8 Ma); 3) strong obliquity pacing prevails in the late Miocene (~7.7-3.3 Ma) following widespread cooling and the increasing influence of high-latitude processes.The lowest %CaCO3 (92-94%) occur between 18.5-14.5 Ma, potentially reflecting increased dissolution or decreased productivity driven by widespread early Miocene warmth. Deposition recovered after the mMCT (~14 Ma), likely associated with changes in regional surface and/or deep-water circulation following Antarctic reglaciation. The highest Site 1264 %CaCO3 and MARs indicate the late Miocene Biogenic Bloom (LMBB) occurs between ~7.8-3.3 Ma. The LMBB’s onset (~7.8 Ma) and peak productivity (~7 Ma) at 1264 are contemporaneous with the LMBB in the equatorial Pacific Ocean; however the termination is ~1 Myr later in the Atlantic compared to the Pacific. Globally synchronous patterns in the LMBB, including the onset and peak, may be driven by an increased nutrient input into the global ocean, for instance from enhanced aeolian dust and/or weathering fluxes. Regional diachrony and variability in the LMBB’s expression may be driven by regional differences in cooling, continental aridification and/or changes in ocean circulation during the latest Miocene.
High-tide flooding in French Guiana due to sea-level rise
Authors: Longueville François , Thieblemont Remi , Idier Déborah , D'anna Maurizio , Bel madani Ali , Le Cozannet Gonéri
Published: February 2023

Many flat coastal plains are already subject to recurrent high-tide flooding events under calm meteorological conditions. As a consequence of sea level rise (SLR), the frequency of such harmful flooding events is expected to increase. Although not catastrophic, the coastal flooding may become a major adaptation challenge as they could cause substantial transportation and economic disruption. In many low-lying coastal zones in the world, an increasing occurrence of high-tide flooding has indeed been recorded. This is often accompanied by land subsidence. The French Guiana coast, located in northern South America, is a coastal plain where nuisance flooding has been recently observed (Cayenne city). In this study, we first performed a hindcast analysis of this recently observed chronic flooding to better understand the associated drivers. Then, we developed projections over the 21st century for three cities of this French territory: Cayenne, Kourou and Mana.Hindcasts and projections of relative SLR (i.e., accounting for vertical land motion) relied on CMIP5 climate model results and IPCC/SROCC estimates for the region, together with records from permanent GNSS stations in French Guiana. The daily maximum tide level was determined from hourly tide gauge observations and tide predictions. SLR and tide water levels combined with digital terrain models have allowed mapping of low-lying areas exposed to coastal flooding, and the associated flooding frequencies.The hindcast analysis revealed the absence of significant land subsidence/uplift and suggested that the recently observed high-tide flooding in Cayenne have been fostered by climate change-induced SLR. Over the 21st century, our results showed that urban zones exposed to high-tide flooding will progressively expand in the three cities, although at different rates. The sectors most exposed to flooding are located along urban channels and within swamps. Conversely, sandy coastlines are less exposed to chronic flooding due to their fast and dynamic evolution in response to changing hydrodynamic forcing factors. The results of this study provide the first scientific basis in French Guiana available for decision-makers and stakeholders in order to develop coastal management and adaptation strategies.
Spatial Hydrology for the Operational monitoring of French Guiana rivers
Authors: Paris Adrien , Gal Laetitia , Calmant Stéphane , Juca Oliveira Romulo , Boussaroque Malik , Gosset Marielle , Gallay Marjorie , Gobinddass Marie-Line , Biancat Celia
Published: February 2023

In a context of a changing climate and an increasing anthropic pressure on natural resources, it is more than ever necessary to maintain or even improve our capacity to understand and monitor inland waters. It is particularly the case in French Guyana, where, despite its relative density, the in situ monitoring network fails at providing everyday information on rivers all over the territory. The use of free and open spatial datasets and hydrological modeling have shown great skills in complementing existing monitoring networks all over the world.  Our work illustrates the use of a hydrological model, namely the MGB, set-up for 10 major watersheds in French Guiana (including the transboundary Maroni and Oyapock River - resp. with Suriname and Brazil- and some smaller ungauged basins) fed on a daily and near-real-time basis by IMERG-RT (Integrated Multi-satellitE Retrievals for GPM - Real Time) remote sensing precipitation products within a scheduler (namely HYFAA). In ungauged basins we used model parameters regionalisation to infer model parameters. The model performed well at inferring discharges, with KGE values higher than 0.7 when compared to gages. An extended dataset of rating curve between water surface elevation from nadir altimetry and simulated discharges is extracted using a physical-based processing of radar echoes on ESA Sentinel3 A&B and Jason3/Sentinel6 missions and also the time series available on Hydroweb website (https://hydroweb.theia-land.fr/). The quality of the rating curves confirms the skill of the model even in ungauged locations and watersheds with small contributive area. Thanks to this set-up, discharges and water levels are estimated daily all over the territory, and routinely corrected by the use of satellite altimetry. Using statistical rainfall predictions and watersheds concentration time, the system allows short-term forecasts of the discharge. In coordination with the in situ network operator, the critical thresholds were defined and are used to trigger  flood and droughts alerts, accessible online and received by email upon registration. As the methods used in this study have largely proved to be deployable anywhere, this simple framework draws the contour of future operational early warning systems based on space observation. 
Changes of Electric Distribution Network Storm Outages in Future Climate Scenarios: Evaluation for a Service Territory in Northeastern United States
Authors: Zhang Xinxuan , Anagnostou Emmanouil , Emmanouil Stergios , Yang Feifei , Cerrai Diego
Published: February 2023

The resilience of electric power system is critical to economic prosperity, as well as public health and safety. In the Northeastern United States, where severe weather events occur throughout the year, it is important to quantify the weather-induced power outages and understand the impact of climate change on power system resilience in the future. This study focuses on assessing the future resilience of the power grid for a service territory in the Northeastern United States, by developing a holistic framework that employs high-resolution climate data along with the power outage prediction models (OPMs). The OPMs are a group of machine-learning based models designed to predict the amount of power outages for different types of weather events. The climate data used in this study are based on selected General Circulation Model (GCM) products that follow two Representative Concentration Pathways (namely RCP 4.5 and RCP 8.5), which are statistically bias-corrected over an 18-km grid. The climate data are, then, used to identify and classify the possible weather-related outage events and quantify associated number of power outages by OPMs. The results aim to, i) quantify the severity and frequency of the occurrence of weather-induced power outages in the next 40 years (2020-2060); and ii) provide a basis for a comparison of the difference of power outages under the two RCP scenarios and the current climate conditions. This information can be useful for making decisions on power grid strengthening plans that accommodate potential future climate change impacts on the power grid resilience. 
Governing equations of slope stability models that consider hydrological and mechanical effect of root reinforcement: A review
Authors: DiBiagio Amanda , Capobianco Vittoria , Oen Amy , Tallaksen Lena M.
Published: February 2023

The use of vegetation as a nature-based solution for shallow landslide risk reduction is receiving increased attention in the scientific community. Vegetation can contribute to slope stability through both hydrological and mechanical root reinforcement, which improves resilience against shallow landslide triggering. In order to quantify the performance of roots as a slope stabilizing measure, slope stability models are valuable tools. Murgia et al. (2022) conducted a thorough review of the existing physically-based models that consider the mechanical effect of roots in the calculation of factor of safety (FoS), suitable for both regional and slope-scale analysis (physically based probabilistic and deterministic models, respectively). This study will build on to the previous review with an in-depth analysis of the equations governing the individuated models that account for the effect of root reinforcement on slope stability. With emphasis also on hydrological effects of vegetation, the governing equations of the different models are analysed and compared, and FoS of an ideal slope case will be assessed by using a selection of the identified models. Finally, this review will serve as a base to develop a guideline which will serve as a tool to ease the decision-making process when deciding which model to use when mitigation measures for a specific slope is to be designed.Reference: Murgia, I., Giadrossich, F., Mao, Z., Cohen, D., Capra, G. F., & Schwarz, M. (2022). Modeling shallow landslides and root reinforcement: A review. Ecological Engineering, 181, 106671.