bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-seismic landslide susceptibility analysis for the Bhagirathi valley of Uttarakhand Himalayan region using machine learning algorithms based on Slope unit techniques
Authors: Gupta Neha , Kanungo Debi Prasanna , Das Josodhir
Published: February 2023

High-magnitude earthquakes are often in seismic zones that initiate the cascading chain of hazards such as co-seismic landslides, soil liquefaction, snow avalanche, surface faulting, devastating rock avalanches, and ground shaking. In the present study, a co-seismic landslide susceptibility analysis was executed for the Bhagirathi valley of Uttarakhand Himalayan region using machine learning techniques based on the slope unit-based method. The study area falls in seismic zone IV, rocks along the fault zone are fragile, and this area is very active seismically. This region has previously experienced Uttarkashi earthquake (1991) of magnitude 6.6. Assessment of seismic induced landslide is considered a complex process, as it considers both static parameters (causative factors) and dynamic parameters (triggering factor) in the form of ground motion shaking effects. In this study, the co-seismic landslide susceptibility maps using the machine learning approach Extreme Gradient Boosting (XgBoost) and Naïve Bayes (NB) techniques have been carried out at Slope Unit-based mapping level. The landslide inventory with 3,000 delineated polygons has been classified into training (80%) and testing (20%) data to calibrate and authenticate the models. For this purpose, static causative factors have been considered, such as slope, aspect, curvature, lineament buffer, drainage buffer, geology, topographic wetness index, and normalized difference vegetation index (NDVI), these parameters have been generated using the CartoDEM and satellite data. Triggering factors Arias Intensity (AI) has been considered for ground motion shaking as a dynamic factor for co-seismic landslides susceptibility mapping. Arias Intensity was prepared using the classical Cornell approach by considering the earthquake catalogue between the years 1700 and 2022. Finally, XgBoost and NB techniques have been used to compute static landslide susceptibility mapping and dynamic co-seismic landslide susceptibility map for a 475-year return period. XgBoost methods at the slope unit level predicted better results. These results were validated using the seismic relative index (SRI) and landslide density method. The prepared map can be effectively helpful for local and regional planning. Keywords: Co-seismic landslide, Slope Unit, Landslide mapping, Machine learning. 
Reviewing numerical simulation methods of nuclear magnetic resonance signals in porous media.
Authors: Soto Bravo Francisca , Zhang Chi , Jia Lin
Published: February 2023

Low-field nuclear magnetic resonance (NMR) is a minimally-invasive geophysical method often used to characterize pore spaces, water content, and fluid transport and distribution in geologic materials. NMR measurements are based on the magnetization and relaxation behavior of the spin magnetic moment of hydrogen atoms in external magnetic fields. These measurements can be taken in the field, such as from a borehole or the surface of the Earth, or in the laboratory using a bench-top apparatus. Numerical simulations of NMR signals are great tools to better understand the relaxation behavior of pore water under different scenarios, explore the effect of changes in the composition or geochemical characteristics of the geologic material, verify experimental findings, and improve the interpretation of field measurements. They can also be used to examine situations where traditional interpretation of NMR signals fails, such as in complex, heterogeneous geometries with pore coupling effects. In a pore coupled system, significant magnetization exchange between pores of different sizes occurs during the measurement time, which makes it difficult to independently characterize the pore environments. Using numerical simulations, it is possible to explore the factors that control pore coupling, such as surface relaxivity, pore-network connectivity and other pore-network characteristics, can be explored independently in a controlled setting. In this work, we introduce common numerical modelling approaches used for simulating NMR responses in geologic materials, along with their limitations and traditional workflows. We present two specific examples: a Random Walk (RW) simulation to test the effect of different pore-network connectivity features on pore coupling in a simplified pore geometry, and a Finite Element Method (FEM) simulation approach to visualize the distribution of magnetization density within a single pore. NMR is a promising hydrogeophysics tool gaining popularity and finding new applications for near-surface exploration. A better understanding of the NMR signals in diverse and complex scenarios is essential for the adequate design of experiments and field campaigns and for the correct interpretation of NMR measurements at different scales. The use of numerical modelling strategies can help improve this understanding, leading to more accurate and reliable measurements and interpretations.
Elmer/Ice results on the CalvingMIPintercomparison project using a level-set function
Authors: Garcia-Molina Cruz , Gillet-Chaulet Fabien , Chekki Mondher , Durand Gael , Gagliardini Olivier , Jourdain Nicolas
Published: February 2023

Ice-calving plays a major role in the mass balance of the water-ending glaciers. Thus, it is crucial to have a well-adapted calving law for simulations over long periods. Due to its dependence on several physical parameters, this phenomenon is usually poorly parametrized in long-term numerical simulations. A worldwide model intercomparison project on ice damage and calving, CalvingMIP (see https://github.com/JRowanJordan/CalvingMIP/wiki), is proposed as part of the European project, PROTECT. The CalvingMIP project aims to evaluate the uncertainties in modelling the ice and to provide recommendations to improve the calving laws in the ice-sheet models. This intercomparison project consists of five experiments using two topographic profiles: a hill and Thule bathymetry. For the first phase, a steady-state configuration is implemented for a fixed calving position. In the second phase: the front velocity is prescribed, forcing the front to advance and, then, to retreat. Finally, the last experiment aims to test a realistic calving law. We study the experiments of this configuration by using the community finite element code, Elmer/Ice (see http://elmerice.elmerfem.org/). We study the front evolution using a level-set function (φ), defined as a signed distance to the front. Here, we present the results obtained with our model for this intercomparison experiment, discuss the sensitivity to different physical and numerical parameters, and its application to a realistic configuration.
Diffuse and concentrated nitrogen sewage pollution in island environments with differing treatment systems
Authors: Alldred Freya , Gröcke Darren , Leung Chung , Wright Lucy , Banfield Nikki
Published: February 2023

Macroalgae is an under-utilised tool as a bioindicator of anthropogenic nitrogen loading to the coastal environment in the UK. This study compared two island systems — Jersey (Channel Islands) and St Mary’s (Isles of Scilly) to assess how differing sewerage infrastructure affects nitrogen loading. A total of 831 macroalgae samples of Fucus vesiculosus and Ulva sp. were analysed for nitrogen isotopes (δ15N). Elevated δ15N values were recorded for Jersey (>9.0 ‰) in St Aubin’s Bay – caused by the outflow from the Bellozanne Sewerage Treatment Works (STW). δ15N isoplots indicate low diffusion of nitrogen from St Aubin’s Bay. St Mary’s produced a varied δ15N isoplot in comparison. δ15N was typically lower and attributed to a smaller population and inefficient STW. Outflow of sewage/effluent at Morning Point, Hugh Town Harbour and Old Town produced elevated δ15N values in comparison to the island average. St Mary’s inefficient sewerage treatment and reliance on septic tanks/soakaways complicates δ15N interpretation although it suggests nitrogen pollution is an issue island wide. Future sewerage development and upgrades on islands are required to prevent the sewage environmental issue in St Aubin’s Bay. This study advocates the use of macroalgae as a bioindicator of nitrogen effluent in the marine environment.
Assessment of the topsoil organic carbon saturation in Hungary using machine learning-based pedotransfer function with uncertainty propagation
Authors: Szatmári Gábor , Jakab Gergely , Laborczi Annamária , Szalai Zoltán , Pásztor László
Published: February 2023

Stakeholders and policymakers have been becoming more and more interested not just in the potential organic carbon (SOC) saturation level of soils but also in spatially explicit information on the degree of SOC deficit, which can support future policy and sustainable management strategies, and carbon sequestration-associated spatial planning. The objective of our study was to develop a cubist-based pedotransfer function (PTF) for predicting and mapping the saturated SOC content of the topsoils (0–30 cm) in Hungary, and then compare this map with the actual SOC map to assess the degree of SOC deficit. It was assumed that topsoils covered by permanent forests can be practically considered as saturated in SOC. Using the monitoring points of the Hungarian Soil Information and Monitoring System located in forests as reference soil profiles, we developed a cubist-based PTF using not just soil properties but also environmental covariates as predictors, and then mapped the saturated SOC content at a resolution of 100 m. We also quantified the prediction uncertainty of the saturated SOC content using first-order Taylor expansion, where not just the uncertainty of the predictors but also the uncertainty associated with the PTF were taken into account. The transparent model structure of cubist allowed to show that not just the physicochemical properties of soils (e.g., texture, pH) but also environmental conditions, such as topography (e.g., slope, altitude) and climate (e.g., temperature, evaporation), characterizing the landscape are important factors in predicting SOC saturation. Our results also pointed out that there is SOC deficit on large part of the country (approx. 80%) showing high spatial variability. It was also revealed that the most considerable potential for additional SOC sequestration can be found related to soils with medium to high actual SOC content.

Acknowledgements: Our research was funded by the National Research Development and Innovation Office (NKFIH), grant numbers: K-123953 and K-131820. The work of Gábor Szatmári was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.
A novel framework for vegetation change characterization from time series Landsat images
Authors: Guo Hancheng , Wang Yanyu
Published: February 2023

Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to reconstructing vegetation change history, investigating change properties, and evaluating the ecological effects. However, current remote sensing techniques are primarily focused on break detection but ignore long-term trend analysis. In this study, we proposed a novel framework based on a change detection algorithm and a trend analysis method that could integrate both short-term disturbance detection and long-term trends to comprehensively assess vegetation change. With this framework, we characterized the vegetation changes in Zhejiang Province from 1990 to 2020 using Landsat and landcover data. Benefiting from combining break detection and long-term trend analysis, the framework showcased its capability of capturing a variety of dynamics and trends of vegetation. The results show that the vegetation was browning in the plains while greening in the mountains, and the overall vegetation was gradually greening during the study period. By comparison, detected vegetation disturbances covered 57.71% of the province’s land areas (accounting for 66.92% of the vegetated region) which were mainly distributed around the built-up areas, and most disturbances (94%) occurred in forest and cropland. There were two peak timings in the frequency of vegetation disturbances: around 2003 and around 2014, and the proportions of more than twice disturbances in a single location were low. The results illustrate that this framework is promising for the characterization of regional vegetation growth, including long-term trends and short-term features. The proposed framework enlightens a new direction for the continuous monitoring of vegetation dynamics.
Towards a satellite based long-term monitoring and prediction of urban heat stress
Authors: Kortschak Dominik , Damm Andrea , Gallaun Heinz , Kernitzkyi Michael , Köberl Judith , Strohmaier Manuel
Published: February 2023

Climate change is causing temperatures around the globe to rise, leading to an increase in hot days and nights and a rise in the frequency and intensity of heat waves. High temperatures represent one of the key factors causing heat stress, which is affecting human health. Examples include the mega heat wave in August 2003 that took more than 70,000 lives across Europe or the unprecedented heat in 2018 with more than 100,000 heat-related deaths in the EU. Spatial exposure to heat stress varies, with urban areas usually heating up much stronger than their rural surroundings (urban heat island effect). With progressing global warming, the importance of spatially monitoring and predicting urban heat stress over large areas to prevent heat-associated morbidity and mortality is thus rising. For this purpose, thermal data obtained by satellites may represent a valuable alternative or addition to in-situ observations and climate modelling, which both show several advantages, but also shortcomings in terms of spatial coverage (in-situ), data needs (climate modelling) and costs.One of the main challenges for the use of satellite thermal data for urban heat stress monitoring is to convert the obtained land surface temperature (LST) into air temperature (AT), since satellites only provide information on the former whereas the latter is needed as input for most heat stress indicators. In our presentation, we will address this challenge with emphasis on urban regions. Two main strands of methods are used in the literature for converting LST into AT. First, data driven methods that use the empirical relationship between in-situ observations of AT from weather stations and LST data from satellites. These methods usually work well for individual stations, but the transferability of the relationship to different locations is typically limited. In addition, especially for methods based on machine learning techniques, a significant amount of data is needed for model calibration. The second type of methods comprises physical models. They typically make use of the energy balance to estimate AT from LST. These models show the advantage of better transferability but need additional input data besides LST. Moreover, physical methods are often designed for applications in rural areas, which may differ from the situation in cities. We apply different methods to derive AT from LST in urban regions and discuss their suitability to monitor and predict urban heat stress based on satellite thermal data.
Accurate forecasting of pollen concentration in real time using machine learning
Authors: Chen Zhuo , Topping David , Crawford Ian
Published: February 2023

The particulate pollutants present in the atmosphere can have a negative impact on human health. Particulate matter consists of biological aerosols (pollen, viruses, etc.) as well as non-biological particles. Among the bioaerosols, research on pollen has been a hot topic in recent years. Pollen allergy is one of the typical clinical symptoms in Europe, with manifestations including but not limited to a runny nose and sneezing. Numerous figures show that the number of people suffering from pollen wind allergies in Europe is increasing year on year, with statistics showing that the prevalence of allergies is now up by 40%. For children, pollen allergies can further lead to serious illnesses such as asthma and eczema.We are now working on time series pollen concentration forecasting and it is also the first real-time pollen concentration data table in England currently. Pollen concentration data is collected every five minutes. Seasonal variations in concentration as well as annual distribution curves have been plotted from this and correlation analysis has been carried out in conjunction with meteorological data to derive relationships between pollen concentrations and meteorological parameters. Accordingly, a suitable time frame will be selected, the data will be substituted into machine learning for training and accurate forecasting results will be produced.  
Continental and oceanic upper mantle thermochemical heterogeneity an density in the European – North Atlantic region.
Authors: Shulgin Alexey , Artemieva Irina
Published: February 2023

We present a joint continental-oceanic upper mantle density model based on 3D tesseroid gravity modeling. On continent lithospheric mantle (LM) density shows no clear difference between the cratonic and Phanerozoic Europe, yet an ~300‐km‐wide zone of a high‐density LM along the Trans‐European Suture Zone may image a paleosubduction. Kimberlite provinces of the Baltica and Greenland cratons have a low‐density (3.32 g/cm3) mantle where all non‐diamondiferous kimberlites tend to a higher‐density (3.34 g/cm3) anomalies. LM density correlates with the depth of sedimentary basins implying that mantle densification plays an important role in basin subsidence. A very dense (3.40–3.45 g/cm3) mantle beneath the superdeep platform basins and the East Barents shelf requires the presence of 10–20% of eclogite, while the West Barents Basin has LM density of 3.35 g/cm3 similar to the Variscan massifs of western Europe. In the North Atlantics, south of the Charlie Gibbs fracture zone (CGFZ) mantle density follows half‐space cooling model with significant deviations at volcanic provinces. North of the CGFZ, the entire North Atlantics is anomalous. Strong low‐density LM anomalies (< −3%) beneath the Azores and north of the CGFZ correlate with geochemical anomalies and indicate the presence of continental fragments and heterogeneous melting sources. Thermal anomalies in the upper mantle averaged down to the transition zone are 100–150 °C at the Azores and can be detected seismically, while a <50 °C anomaly around Iceland is at the limit of seismic resolution. Presented results is a further development of the EUNA-rho model (doi:10.1029/2018JB017025)
Developments to 2D modelling of ice island deterioration using the CI2D3 Database
Authors: Crawford Anna , Crocker Greg , Mueller Derek , Smith Jesse
Published: February 2023

The calving of ice tongues and ice shelves can generate large, tabular icebergs that have climatological implications given their role in dispersing freshwater from the Greenland and Antarctic ice sheets. These ‘ice islands’ also pose potential risk to marine industry. It is therefore critical that influential deterioration mechanisms be accurately represented in simulations of ice island drift and deterioration, both for risk mitigation in offshore industry and for climatological studies that are focused on the Polar Regions. The majority of ice island deterioration is the result of sidewall erosion, and specifically that which results from waterline wave-erosion leading to ram growth and buoyancy-forced fracture. This study therefore focuses on the inclusion of the buoyancy-driven “footloose” calving mechanism (Wagner et al., 2014) in simulations of ice island length and areal change. Using size and lineage information of ice islands tracked in the Canadian Ice Island Drift, Deterioration and Detection (CI2D3) Database, we quantitatively assess the performance of the footloose calving model by simulating the deterioration of 172 ice islands. The mean model error was +15 (+/- 400) m over 20 d and increased to +401 (+1400/-800) m for simulations that ran to 80 d. The performance of the footloose calving model is a substantial improvement when compared to simulations that did not include this calving mechanism. For example, a thermal-melt model had mean errors of -252 and -1403 m at 20 and 80 d of simulation, respectively, and the mean error of a zero-melt model was -281 and -1545 m over the same time periods. We also present a new approach to modelling ice island areal change resulting from footloose calving. This simple, two-parameter approach simulates discrete footloose calving events and adjusts the ice island surface area to maintain a constant aspect ratio. Mean model error remained under 1 km2 over 80 d of simulation, showing that the model performs well over numerous months. Using the CI2D3 Database, we were able to conduct the first large-scale assessment of the footloose model’s performance in simulating change to the ice island length dimension. The morphological data included in the database also provided the opportunity to develop an approach for modelling areal deterioration resulting from footloose calving events. The model assessments would benefit from more observations of long-duration ice island tracks, as there were a limited number of ice islands that were tracked in the CI2D3 Database for over 40 d. Future work can look to implement the presented approaches in operational and climatological modelling while the iceberg modelling community also develops an approach to simulate larger-scale ice island fracture.
Depth dependence of coseismic off-fault damage
Authors: Ferry Roxane , Thomas Marion , Jeandet Louise
Published: February 2023

Faults are complex systems embedded in an evolving medium fractured by seismic ruptures. This off-fault damage zone is shown to be thermo-hydro-mechano-chemically coupled to the main fault plane by a growing number of studies. Yet, off-fault medium is still, for the most part modelled as a purely elastic -- hence passive -- medium. Using a micromechanical  model we investigate the depth variation of dynamically triggered off-fault damage and its counter-impact on earthquake slip dynamics. We show that if the damage zone becomes narrower with depth, it is also denser and thus, unlike what is commonly believed, remains an energy sink even at depth. The results are in agreement with the complementary model by Okubo et al., 2019. In contrast to study cited above, our model accounts for the dynamics changes of elastic moduli related to crack growth. This lead to the dynamic creation of low-velocity zone that can trapped seismic waves and further impact the earthquake dynamics, even at greater depth. We therefore claim that the intertwined dynamics between the main fault plane and its surrounding medium must be including along the all seismogenic.
How Climate Change influence groundwater temperature? A case study in the Piedmont Po Plain (NW Italy)
Authors: Egidio Elena , Mancini Susanna , De Luca Domenico Antonio , Lasagna Manuela
Published: February 2023

This study represents the first regional-scale investigation in the Piedmont Po plain about the relationship between groundwater temperature in the shallow aquifer (GWT) and climate variability. The aim of this investigation is to study and compare time trends in air temperature (AT) and GWT over a 10-year time period (between 2010 and 2019), and to evaluate possible relationships between the two parameters. For doing so we had used daily measures taken from 41 monitoring wells located in the shallow aquifer and 20 weather stations throughout the Piedmont Po plain area.Both AT and GWT showed an increase over the observed period with a more pronounced growth of the AT. With regard to AT all the weather stations had shown an increasing trend with a variation in the annual mean 1.7 and 2.2 ◦C/10 years; moreover, GWT annual mean generally shows a variation between −0.3 and 2.1 ◦C/10 years. This result allows to state that GWT is more resilient to climate change than AT. However, some monitoring wells in the study area showed a behaviour that partially deviated from the standard trend observed for the majority of the region: these wells were influenced by particular anthropic factors (for example the paddy fields) or natural elements (as the monitoring wells located downstream of melting glaciers, or the wells located close to Rivers). Further investigations will be conducted in future in Piedmont plain areas with different behaviour, in order to better understand their dynamics and the factors that may influence GWT and how they are affected by climate change.Moreover, this study wanted to stress the importance of the knowledge of the localization in wells of the instruments for the GWT measurement, to have the most accurate and comparable data. As already state in literature the GWT fluctuation in the bottom part of the aquifer was milder than the fluctuation observed in the most superficial part. Therefore, it has been possible to observe that in the study area when the depth of the instrument increased, the maximum and minimum peaks of the GWT shifted in time respect to the maximum and minimum peaks of the AT.Lastly, we are conducting a groundwater and heat flow simulation of the shallow aquifer of the Turin Plain area using a numerical model with Smoker Heatflow code. The calibration performed with the available hydrogeological setting information of the area and the GWT and AT data will allow us to model the future spatial distribution of GWT in the study area, according to the IPCC forecast scenarios.
Physical processes controlling warm conveyor belt moisture transport to the UTLS and dependence on model resolution
Authors: Schwenk Cornelis , Miltenberger Annette
Published: February 2023

Warm conveyor belts (WCB) are regions of large-scale coherent airflow within extratropical cyclones that rapidly ascend from the boundary layer to the upper troposphere. During their ascent, WCBs transport water vapour and cloud condensate to the upper troposphere, and thereby significantly contribute to the moisture content of the extra-tropical upper troposphere-lower stratosphere (UTLS) as well as upper tropospheric cloudiness. UTLS moisture content and cloudiness are important for the radiative budget of the Earth and future changes thereof, but are often poorly represented in numerical models and reanalysis products. A detailed quantitative understanding of the processes governing water transport in WCBs provides vital clues to the origin of these biases and for evaluating predicted future changes in WCB moisture transport. Furthermore, recent studies have found that deep and embedded convection play an important role in WCBs. This points to the necessity of high-resolution simulations, that are well validated with observational data to provide a “benchmark” for coarser-resolution global (climate) models. Here we investigate the physical processes governing WCB moisture transport in simulations of a case-study from the WISE campaign with a particular focus on (i) the impact of grid spacing (including the use of convection parameterisations) on WCB moisture transport, (ii) the microphysical processes controlling moisture loss from the WCB, and (iii) the cloud microphysical properties of the cirrus clouds in the WCB outflow.To this end we conducted two ICON simulations of an extratropical cyclone using (i) a global (~13km resolution), convection-parameterizing and (ii) a doubly nested (~13km, ~6km and ~3km resolution) convection permitting set up. In both set-ups online trajectories are calculated that capture convective ascent and allow for a Lagrangian analysis of WCB moisture transport and WCB cloud structure.The Lagrangian metrics show large differences in ascent timescales and the efficiency with which water is transported from the boundary-layer to the UTLS. It is shown that this impacts the UTLS moisture content in the WCB outflow region. Local changes in UTLS moisture content induced by different representations of convection are shown to project onto larger-scale structures in the moisture and cloud fields over the 1-2 days after WCB ascent.
Modelling sea salt aerosol flux from blowing snow over a changing sea ice environment
Authors: Ranjithkumar Ananth , Duncan Eliza , Yang Xin , Partridge Daniel , Frey Markus
Published: February 2023

A quantitative understanding of climate change in the polar regions being more extreme than at lower latitudes requires monitoring and modelling of key climate variables in these regions. Climate models disagree with observational datasets on the magnitude of the rate of Arctic amplification, and the representation of the chemistry and microphysics of aerosol particles in models is one of the contributing factors to the uncertainty in predicting polar climate. Aerosols represents one of the key model uncertainties through its impact on the surface energy balance via the scattering and absorption of solar radiation, and by its ability to influence cloud microphysics. Sea salt aerosol originating from the sublimation of blowing snow is a newly discovered source of aerosol particles above sea ice during winter and spring, and the hypothesised formation mechanism has been validated recently in the Antarctic. However, the lack of observations over a wide range of sea ice conditions including sub-micron sized particles has been a barrier towards accurately quantifying the mechanism of formation of SSA and the resulting SSA mass flux. Moreover, current blowing snow model parameterisations do not consider the spatial and temporal variability of sea ice and atmospheric state, which has a strong impact on the strength of the particle source from blowing snow across individual storms. In this study, we use observations from the MOSAIC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition (Oct 2019 to Sept 2020) and N-ICE2015 (Feb-June 2015) in the Arctic, and Weddell Sea measurements (June-October 2013) in the Antarctic to better constrain the blowing snow sea salt flux. We consider snow particle size distribution and snow salinity, which are both sensitive model parameters that govern the sea salt aerosol flux over sea ice. A gamma distribution fit is used to characterise the snow particle size distribution as a function of the 10-meter wind speed (ranging from the threshold wind speed (~5ms-1) to 15ms-1). Using the observations, we were able to better constrain the shape parameter of the gamma distribution, alpha, when compared to past studies.  We discuss the relationship between snow salinity and snow depth, to capture the influence of the changing sea ice and snowfall on blowing snow aerosol source. We implement these parametrisations derived from point measurements into a chemistry transport model (p-TOMCAT) to better capture the spatially and temporally variable blowing snow source across polar regions, which helps to accurately simulate the aerosol number and mass concentration, and sodium concentration in polar regions.
Insights into the hydrology of the Congo peatlands through land surface modeling and data assimilation
Authors: Apers Sebastian , De Lannoy Gabriëlle , Cobb Alexander R. , Dargie Greta C. , Reichle Rolf H. , Bechtold Michel
Published: February 2023

The 16.8 million ha of peatlands in the Cuvette Centrale wetland complex in the Congo Basin is one of the largest peatland regions on Earth but still highly understudied. Understanding the hydrological functioning of these peatlands and the effects of external disturbances thereon remains a major challenge. Recent research suggested fundamental hydrological differences between the Congo peatlands and the well-studied Southeast Asian peatlands. The Congo peatlands have a doming gradient that is up to ten times smaller, and they are influenced by river hydrology to some extent.In this study, we explore the Congo peatland hydrology through land surface modeling and data assimilation. We build upon our recently developed tropical PEATCLSM module (Apers et al., 2022) that was parameterized based on data from Southeast Asian peatlands due to the lack of field data from other tropical peatland regions. In a first step, we derive Congo-specific peat hydraulic and discharge function parameters from a scalar parametrization of water level dynamics in the Congo peatlands, using observed water level data at two locations. These Congo-specific parameters differ considerably from the original literature-based parameters from Southeast Asian peatlands. In a second step, we apply our original and Congo-specific parameters in an assimilation scheme for L-band brightness temperature (Tb) data from the Soil Moisture and Ocean Salinity (SMOS) mission. The data assimilation results are used in two ways. First, the effect of these parameters on the simulated peatland hydrology and the observation-minus-forecast Tb residuals is evaluated. It is hypothesized that the new parameters reduce the previously reported modeling errors over the Congo peatlands and reduce the residuals in Tb as well. Second, we analyze the data assimilation diagnostics to learn about other model improvement possibilities. In preliminary results, we found long periods of temporally autocorrelated total water storage increments (difference of pre- and post-update) that coincided with anomalies in river stages measured upstream of the peatlands. Since PEATLCSM neglects possible river influence, this concurrence suggests that the typically used grid-based approach of land surface models should be combined with a river routing scheme over the Congo peatlands.Apers, S., De Lannoy, G. J. M., Baird, A. J., Cobb, A. R., Dargie, G. C., del Aguila Pasquel, J., ... & Bechtold, M. (2022). Tropical peatland hydrology simulated with a global land surface model. Journal of advances in modeling earth systems, 14(3), e2021MS002784.
Detecting hydromorphological structures using an AI-based analysis of high-resolution drone imagery to access physical river habitat development
Authors: Dacheneder Felix
Published: February 2023

The detection of hydromorphological structures gained more attention during the last decades. Many approaches of different scopes, scales and purposes have been developed. They can either be classified as stand-alone methods, like the German River Habitat Survey, which evaluates the hydromorphological integrity on a catchment scale or as methods being part of an ecological assessment, which includes the estimation of hydromorphological characteristics on the scale of respective study sites. The main purposes of detecting hydromorphological structures are to investigate the spatial characteristics and temporal scale of change to collect reliable and comparable data in a sampling setup of an ecological multi habitat sampling. Especially river restoration projects often lack the detection of positive effects on aquatic biota induced by missing or wrong development of physical river habitat structures (PRHS).Most methods available for determining PRHS are insufficient for this task as they lack sufficient temporal and spatial resolution. Examples thereof include overview methods based on topographic maps and remote sensing. On the other hand, visual assessment methods do not reach the required accuracy and objectiveness or are too general if too few hydromorphological structures are assessed. Therefore, this research proposes the combination of Unmanned Areal Vehicle (UAV) and high-resolution sensors. This combination creates high-resolution imagery or point clouds by using multispectral sensors or Lidar scanner.In a case study of the river Lippe, the methods for detecting PRHS on Structure from Motion (SfM) high-resolution imagery with deep learning, based classification methods are applied. Results indicate the potential from different deep learning classification approaches to identify physical river habitat structures being able to assess the development over time.
Field observations of Infragravity waves along the Belgian coast
Authors: Pepi Yuri , Ponsoni Leandro , Boone Wieter
Published: February 2023

Infragravity waves have been identified as driving force behind various nearshore processes including beach and dune erosion, the development of seiches in harbors, and wave-driven coastal inundation when not accounted for in the design calculations. These waves have been observed to cause extreme water levels and resulting damage in various locations around the world.Field observations and measurements are essential for understanding the behavior and impacts of infragravity waves, which are long surface waves with low and with significantly longer periods than the peak frequency of the incident wave spectrum. The period is typically between 30 and 300 seconds (0.03 – 0.003 Hz), the amplitude ranges from a few millimeters to tens of centimeters and has a wavelength scale of kilometers.In this study, we first revisit field observations, instrumentation, and sampling techniques that have been used to study this phenomenon. The advantages and limitations of different approaches are discussed, as well as the challenges and best practices for collecting high-quality data in the field are addressed.Field observations were conducted using multipurpose mooring frames equipped with both ADCP-based acoustic surface tracking and high-accuracy quartz pressure sensors. Data were collected continuously for 3 months, covering storm and moderate wave conditions. The measurements from ADCP and pressure sensor were combined and the infragravity wave characteristics were determined. Algorithms to calculate the wave characteristics were developed and combined with data from tide gauges and wave buoys to calibrate the sensors and cross-validate the results.The observations showed that infragravity waves can be effectively monitored using ADCP and high-accuracy quartz pressure sensors, providing useful information regarding impacts on the coastal environment. The results showed the relevance and occurrence of these waves along the Belgian coast and valuable insights into their generation and propagation and the interaction with Sea-swell waves, including with relation to their spatio-temporal variability.
On the exploitation of L-band DInSAR products retrieved through the SAOCOM-1 constellation for the investigation of natural and anthropogenic hazards.
Authors: De Luca Claudio , Roa Yenni Lorena Belen , Bonano Manuela , Casu Francesco , Franzese Marianna , Manunta Michele , Muhammad Yasir , Onorato Giovanni , Striano Pasquale , Zinno Ivana , Lanari Riccardo
Published: February 2023

Differential Synthetic Aperture Radar Interferometry (DInSAR) is a well-known technique that allows the investigation of surface displacements affecting large areas on the Earth, in both natural and anthropogenic hazard scenarios, with limited costs and with a centimeter to millimiter accuracy. In the last decades the effectiveness of the satellite DInSAR technology for ground deformation analyses, and its crucial role in emergency scenarios, have been largely demonstrated, thus pushing the space agencies to develop new space-borne SAR systems. In particular, important investments on the development of L-band SAR systems are ongoing, with the forthcoming missions of ESA (ROSE-L), JAXA (PALSAR-3) and NASA-ISRO (NISAR), as well as the already operating SAOCOM-1 and PALSAR-2 systems clearly showing the relevance of these sensors, particularly for what attains their DInSAR applications. Indeed, it is worth to remark that the L-band DInSAR interferograms are effective in maintaining coherence for a long period over rather vegetated areas and in various cases of snow/ice covered zones, thus allowing to overcome the typical limitations of higher frequency systems, operating at C- and/or X-band, which, in the above scenarios, typically guarantee sufficient coherence only for a few weeks.In this work, we present the first results achieved by processing stripmap L-band SAR images acquired by the Argentinian SAOCOM-1 constellation. In particular, we show some algorithmic developments made for an efficient DInSAR exploitation of stripmap SAOCOM-1 images. These improvements can play a significant role in different scenarios as for creating a national scale L-band ground motion service and for civil protection purposes, thanks to the potential capability to provide, in several portions of Earth, systematic space-borne L-band products with a revisit time, typically, of 24 days that can be reduced down to 8 days. Finally, we present the surface displacement maps and time-series retrieved through the Parallel Small BAseline Subset (P-SBAS) processing chain, properly adapted to process the SAOCOM-1 images, over some selected areas of interest, which involve both volcanic hazard contexts (Campi Flegrei caldera and Etna and Stromboli volcano in Italy), and fast-/slow-moving hydrogeological phenomena (Zeri, Tuscany region and Garessio, Piemonte region, in Italy).The activities of this work were carried out within the project referred to as DInSAR-3M, funded by the Italian Space Agency (ASI), which is aimed at generating, through advanced DInSAR methodologies, surface deformation time series and mean velocity maps, spatially and temporally dense, for the multi-scale analysis of natural and anthropogenic phenomena.
Quantification of the Radiative Effect of Arctic Cirrus by Airborne Radiation Measurements - A Case Study
Authors: Röttenbacher Johannes , Müller Hanno , Ehrlich André , Wendisch Manfred
Published: February 2023

Observations of cloud related processes in the Arctic are needed to evaluate the representation of clouds in weather and climate models and to improve our understanding of processes of Arctic amplification and Arcitc-midlatitude linkages. One remaining uncertainty of the Arctic climate system are cirrus clouds and their influence on the radiative budget. Arctic cirrus is known to warm the climate system on annual average, especially when present over the sea ice covered central Arctic. The HALO-(AC)³ airborne campaign in spring 2022 investigated changes within air masses on their way in and out of the central Arctic with the High Altitude LOng Range research aircraft (HALO), which was equipped with a suite of remote sensing instrumentation. Two flights were used to explicitly investigate the cloud radiative effect of single layer isolated cirrus between 81 and 90 degrees North.Flight legs above and below the cirrus with measurements of spectral solar irradiance from the Spectral Modular Airborne Radiation measuremenT system (SMART) make a direct estimation of the cloud radiative effect possible. The cirrus was sufficiently thick to reduce the transmission of solar radiation by around 25%. However, significant inhomogeneities in the cirrus were observed.We present a case study of the radiative effect of Arctic cirrus and compare airborne irradiance measurements to simulations from an offline run of the ecRad radiation scheme which is operationally used in the ECMWF's Integrated Forecasting System.
Relative locations and moment tensors of the Nord Stream pipeline events
Authors: Köhler Andreas , Alvizuri Celso , Dando Ben , Goertz-Allmann Bettina , Schweitzer Johannes , Oye Volker , Lund Björn , Schmidt Peter , Roth Michael , Eggertsson Gunnar , Larsen Tine B. , Voss Peter H. , Dahl-Jensen Trine , Rinds Nicolai , Weidle Christian
Published: February 2023

Two clear seismic events were observed on 26th September 2022 associated with the reported leaks from the Nord Stream 1 (Event 1, NE of Bornholm) and Nord Stream 2 pipelines (Event 2, SE of Bornholm). Arrivals of both events were detected and associated using data from several arrays in Norway and Finland, including the IMS stations NOA, FINES and ARCES. Additional signal analysis with data from the Swedish National Seismic Network and the Danish station on Bornholm enabled a third event to be identified. Auto-correlation analysis of the Event 2 revealed the third event (Event 2B) about 7 seconds after the main amplitude of the P onset (Event 2A). In contrast, for Event 1 SE of Bornholm no additional events could be identified from auto-correlation analysis, which increases confidence that these additional arrivals are not caused by interaction with geological structures. We also observe an arrival 7 s after the Pn phase before the Pg arrival on the NORES array. However, we cannot exclude that this onset interferes with the arrival of the PnPn phase. We then use the time differences between Event 2A and 2B measured by auto-correlation analysis on the Swedish and Danish network stations to determine relative epicentre locations. The results suggest that the two overlapping events occurred just about 220 m apart from each other. The relative locations fit very well with the distance between both pipelines of Nord Stream 1 at the Westernmost gas plume location (NE of Bornholm). We also estimated preliminary full moment tensors for Event 1 and 2 using seismic waveform data and analysed them on a source-type diagram. The results show positive isotropic parameters consistent with explosion-type mechanisms.
Assessment of land energy uptake in the industrial period from observation and simulation-based products
Authors: García-Pereira Félix , González-Rouco Jesús Fidel , Steinert Norman Julius , Melo-Aguilar Camilo , de Vrese Philipp , Jungclaus Johann , Lorenz Stephan , Hagemann Stefan , García-Bustamante Elena
Published: February 2023

Under increased warming from ongoing anthropogenic climate change, the land acts as an energy sink for the climate system, interacting with the atmosphere at a wide range of time scales. Based on CMIP multi-model comparisons, the latest estimates of the global energy budget quantify the land contribution to be 2% in the last six decades, whereas other studies based on borehole temperature profiles scale it up to 5%. This discrepancy is suspected to stem from state-of-the-art CMIP land surface models using a shallow zero flux bottom boundary condition placement (BBCP) that severely constrains land energy storage by halting ground heat flux penetration at the BBCP depth and biasing subsurface thermal structure. A 2000-year-long (past2k) forced simulation using a version of the Max Planck Institute (MPI) Earth System Model (ESM) with a deep BBCP (1417 m) was performed to assess the behavior of subsurface temperature and energy storage at long-term scales. Results show that land energy uptake is 4 times higher in a coupled MPI-ESM simulation with a deep version of the land component compared to standard shallow (~10m) simulations. These estimates are well above those provided by CMIP6 models and are much closer to observations, underlining the importance of BBCP-depth in correctly representing the role of the land component in the global energy budget. The results of the analysis of the past2k simulation also allow for deriving reliable estimates of land energy uptake from other observational and reanalysis products as well as providing corrected estimates for the shallow LSM CMIP6 historical and scenario simulations. Land energy uptake estimates rendered from this new approach are much closer to previous BTP-based estimates and agree with the value derived from MPI-ESM deep simulation.