bluuebunny/crossref_metadata_2025 huggingface dataset:
Movement of moisture during frost cracking cycles: First laboratory results from the CLIMROCK project.
Authors: Mitchell Andrew , Sass Oliver
Published: March 2022

As a key part of landscape evolution and hazard to people in Alpine terrain, rock weathering leads to the breakdown and weakening of rock, causing rock fall and ultimately slope failure. Rock moisture availability is a major factor in these processes. It is understudied, partly due to a lack of reliable measurement techniques. Most frost weathering tests in the laboratory to date have been conducted with fully saturated specimens, which is often not the case under natural conditions.

As part of the DFG-funded CLIMROCK project, we performed laboratory based experiments in a climate cabinet looking at rock moisture movement during frost cracking cycles and its relation to rock weathering. A selection of Wettersteinkalk (limestone) blocks of 40 x 40 x 20 cm size were used, some of which were compact and some of which were highly fractured. The blocks saturated with water to different degrees (0%, 50%, 100%) and were insulated on the side faces. In different test runs, the base of the individual blocks were either left uncovered to allow water seeping through, also isolated at the base to create Different sensor types including Time Domain Reflectometry (TDR), Electrical Resistivity (ER) and Microwave sensor (MW) were used to quantify rock moisture levels and movement during freeze-thaw cycles of different duration. As a measure of relative rock weathering contact Acoustic Emissions (AE) loggers were used to detect subcritical cracking. Calibration of these instruments will be individual to each block.

Initial findings show marked movement of rock moisture at the beginning of the cycles with possible evidence of cryosuction down to 36cm depth from rock surface. Particularly strong moisture migration is seen in 50% and 100% samples at 25cm depth, though not when the sample is initially dry. There is also evidence of migrations to the freezing front and probable subsequent refreezing events.

Further test runs with different saturation levels (75%, 90%) are planned. Observations of moisture movements and weathering effects from the laboratory experiments will be applied to the interpretation of field rock moisture data from ongoing CLIMROCK studies in the Bavarian and Austrian Alps.
Effect of underestimation/overestimation of falling drop parameters on the result of splash simulation in an immiscible liquid system
Authors: Sochan Agata , Lamorski Krzysztof , Bieganowski Andrzej
Published: March 2022

The phenomenon of multiphase splash can be a mechanism for transporting various types of pollution (e.g. petroleum substances), which makes it especially interesting in the context of environmental protection.

In this paper, the water splash phenomenon caused by the impact of a petrol drop on the water surface was simulated using the multiphaseInterFoam solver, i.e. a part of the OpenFOAM computational fluid dynamics software implementing the finite volume method (FVM) for space discretization. The simulations were experimentally validated based on splash images obtained with the use of a high-speed camera (2800 fps). Several variants of simulations with a varying drop size (in 0.10-mm steps) or drop velocity (in 0.025-m/s steps) were conducted.

Our experiments showed the importance of even a slight underestimation/overestimation of the properties of a falling drop on the simulation of the size and dynamics of splash in an immiscible liquid system. On the other hand, correct simulation made it possible to analyse aspects of the phenomenon that were difficult or even impossible to achieve experimentally due to the limitations of the image analysis method. This concerned the determination of the cavity width, the moment of cavity disappearance, the moment of jet formation (still below the water level), and the height of the jet. In addition, based on the validated simulation of splash in immiscible liquids, the scale of the spread of petroleum contamination as a result of the impact of a single droplet was determined.

The study was partly funded by the National Science Centre (Poland), based on decision no. 2017/26/D/ST10/01026.
FAIR WISH - FAIR Workflows to establish IGSN for Samples in the Helmholtz Association
Authors: Baldewein Linda , Elger Kirsten , Heim Birgit , Brauser Alexander , Frenzel Simone , Kleeberg Ulrike , Norden Ben
Published: March 2022

The International Geo Sample Number (IGSN) is a globally unique and persistent identifier (PID) for physical samples and collections with discovery function on the Internet. IGSNs enable to directly link data and publications with samples they originate from and thus close the last gap in the full provenance of research results. The modular IGSN metadata schema has a small number of mandatory and recommended metadata elements that can be individually extended with discipline-specific elements.

Based on three use cases that represent all states of digitisation - from individual scientists, collecting sample descriptions in their field books to digital sample management systems fed by an app that is used in the field - FAIR WISH will (1) develop standardised and discipline specific IGSN metadata schemes for different sample types from the Earth and Environment Sciences, (2) develop workflows to generate machine-readable IGSN metadata from different states of digitisation, (3) develop workflows to automatically register IGSNs and (4) prepare the resulting workflows for further use in the Earth Science community.
From up above to down below: Comparison of satellite- and ground-based observations of SO2 emissions from the 2021 eruption of Cumbre Vieja, La Palma
Authors: Hayer Catherine , Barrancos José , Burton Mike , Rodríguez Fátima , Esse Ben , Hernández Pedro , Melián Gladys , Padrón Eleazar , Asensio-Ramos María , Pérez Nemesio
Published: March 2022

Volcanic gas emissions are an integral part of volcano monitoring around the world and can be interpreted to understand the state of a volcano and the evolution of an individual eruption. The low ambient concentrations of SO2 make it an ideal monitoring candidate.

Throughout the 2021 eruption of Cumbre Vieja, La Palma (Spain), observations of SO2 emissions were made using ground-based instruments, in transverse mode, static scanners and on-board drones, as well as by numerous satellite instruments. Direct comparison between satellite- and ground-based instruments is always challenging, but the long duration of the eruption and repeated measurements from both data sets made this a good candidate.

Data from the Sentinel-5P instrument TROPOMI was combined with the PlumeTraj back-trajectory analysis toolkit to produce sub-daily SO2 fluxes that can be directly compared to the ground-based observations as well as other geophysical and geochemical monitoring data.

The volcano produced significant volcanic ash emissions, particularly in the earlier phases of the eruption, which impacted both ground- and satellite-based measurements. This produced underestimations in the SO2loading where ash was present, impacting the proximal plume more that the distal as the ash settles out with time. This meant that traverse measurements were more impacted, leading to a disparity in the measured fluxes from ground and space. Later, when ash emissions had decreased, the agreement between the two was much improved, with trends closely replicated between the traverse and satellite fluxes.

The initial estimates of the total SO2 emission from the eruption were 4.1 Mt from TROPOMI and 1.2 Mt from the traverse data.

These measurements formed part of the official monitoring effort, providing insights into the eruption’s evolution and informing the civil defence response throughout the eruption.
Possible controls on Arctic clouds by natural aerosols from  long-range transport of biogenic emissions and ozone depletion events
Authors: Holzinger Rupert , Eppers Oliver , Adachi Kouji , Bozem Heiko , Hartmann Markus , Herber Andreas , Koike Makoto , Millet Dylan , Ohata Sho , Stratmann Frank
Published: March 2022

During the PAMARCMiP 2018 campaign (March and April 2018) a proton-transfer-reaction mass spectrometer (PTR-MS) was deployed onboard the POLAR 5 research aircraft and sampled the High Arctic atmosphere under Arctic haze conditions. More than 100 compounds exhibited levels above 1 pmol/mol in at least 25% of the measurements. We used back trajectories and acetone mixing ratios to identify periods with and without long-range transport from continental sources.

Air masses with continental influence contained elevated levels of compounds associated with (aged) biogenic emissions or aged anthropogenic pollution (e.g., methanol, peroxyacetylnitrate (PAN), acetone, acetic acid, methylethylketone (MEK), proprionic acid, and pentanone), but benzene – a marker for primary pollution – was not enhanced. Almost half of all positively detected compounds (>100) in the High Arctic atmosphere can be associated with terpene oxidation products. This constitutes a strong signature of biogenic terpenes and their oxidation products on the High Arctic atmosphere. Many of these compounds will condense and produce biogenic secondary organic aerosol (SOA) – a natural source of organic aerosol (OA) in addition to the aerosols that can be associated with anthropogenic pollution. Therefore, we hypothesize that biogenic SOA exerted significant control over the complex system of aerosols, clouds and longwave radiation in the pre-industrial Arctic winter, even though their role is likely marginal under contemporary polluted Arctic haze conditions. However, biogenic SOA may become an important factor in the future again, if biogenic emissions are enhanced due to climate change and if polluting technologies are (hopefully) phased out in the near future.

During two flights, surface ozone depletion events (ODE) were observed that coincided with enhanced levels of acetone, and methylethylketone. There is evidence that ODEs may also be associated with the emission of biogenic ice-nucleating particles (INP) because the filter samples taken during these two flights exhibited enhanced levels of highly active ice-nucleating particles (INP).

Both these processes, INP production in association with ozone depletion events, and the transport of biogenic SOA could require corrections in estimates of preindustrial radiative forcing (RF). If preindustrial RF has been stronger, the Arctic amplification would be even stronger than currently assumed.
Channelizing of melt flow by reactive porosity waves and its impact on chemical differentiation
Authors: Frendak Andrey , Alkhimenkov Yury , Khakimova Lyudmila , Utkin Ivan , Podladchikov Yury , Schmalholz Stefan
Published: March 2022

Many geodynamic processes are coupled. For example, in the partially molten mantle, the solid and molten mantle phases interact chemically during porous melt flow. For such two-phase reactive melt migration, solid and melt densities are functions of temperature, pressure, and chemical composition. Numerical models of such coupled physical-chemical systems require special treatment of the various couplings and concise numerical implementation. We elaborate a 2-D thermo-hydro-mechanical-chemical (THMC) numerical model for melt migration by porosity waves coupled to chemical reactions (Bessat et. al., 2021). We consider a simple ternary chemical system of forsterite-fayalite-silica to model melt migration within partially molten peridotite around the lithosphere-asthenosphere boundary. Our THMC model can simulate porosity waves of different shapes depending on the ratio of shear to bulk viscosity and the ratio of decompaction to compaction bulk viscosity. For an initial circular (blob-like) porosity perturbation, having a 2-D Gaussian shape, the geometry of the propagating reactive porosity wave remains blob-like if all viscosities are similar. If the decompaction bulk viscosity is smaller than the compaction bulk viscosity, so-called decompaction weakening, then the propagating porosity wave evolves into a channelized form. Our simulations quantify the variation from a blob-like to a channel-like porosity wave as a function of the viscosity ratios. We describe the 2-D THMC numerical algorithm which is based on the pseudo-transient finite difference method. Furthermore, we quantify the impact of channelization on the chemical differentiation during melt flow. Particularly, we quantify the evolution of the total silica concentration during melt migration as a function of the degree of channelization.

References

Bessat, A., Pilet, S., Podladchikov, Y. Y., & Schmalholz, S. M. (2022). Melt migration and chemical differentiation by reactive porosity waves. Geochemistry, Geophysics, Geosystems. In press.  
Pollen-based reconstruction of regional vegetation and land cover in the Northern Hemisphere
Authors: Schild Laura , Ewald Peter , Böhmer Thomas , Postl Alexander Karl , Li Chenzhi , Laepple Thomas , Herzschuh Ulrike
Published: March 2022

Data on past vegetation compositions is crucial not only for understanding past vegetation dynamics and environmental interactions but also for predicting potential future vegetation trajectories and thus their feedback on climate and society. Pollen records from sediment cores provide temporally resolved data on pollen frequencies. These allow for inferences of taxa presence, but biased pollen deposition due to taxa-specific pollen productivity and dispersal prohibit direct inference of taxa abundance.

The model for Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) corrects for these taxa-specific parameters and produces more realistic regional vegetation abundances. Previously applied in many regions such as North America, Southern Sweden, Norway, and more recently the entirety of Europe, REVEALS has performed well in providing estimates for large vegetation units as well as individual taxa. 

With this data set, we present reconstructed past regional vegetation for more than 2200 sites across the Northern Hemisphere. The REVEALS model was applied by using a harmonized pollen dataset for the entire Northern Hemisphere, taxa-specific pollen productivity estimates, pollen fall speeds, as well as pollen dispersal models. First validations show an improved fit of the reconstructed vegetation with remotely sensed tree cover compared to pure pollen percentages. For validation tree cover datasets from the CONSENSUS global 1-km land cover product were used. The pollen source areas were defined to include 80% of the area from which deposited pollen originated.

This first-time reconstruction for the entire Northern Hemisphere will allow for detailed analysis of vegetation dynamics and trajectories ultimately improving our understanding of climate-vegetation interactions, and may even act as input and validation for other vegetation and climate models and proxies.
Monitoring volcanic plume height and fountain height using webcameras at the 2021 Fagradalsfjall eruption in Iceland
Authors: Barnie Talfan , Titos Manuel , Hjörvar Tryggvi , Bergsson Bergur , Pálsson Sighvatur , Oddson Björn , Barsotti Sara , Pfeffer Melissa , von Löwis of Menar Sibylle , Sigurðsson Eysteinn , Arason Þórður
Published: March 2022

The 2021 Fagradalsfjall basaltic fissural eruption in Iceland was closely studied due to its proximity to Reykjavík, which allowed easy installation and maintenance of monitoring equipment. Here we present the results from a network of calibrated webcameras maintained by the Icelandic Meteorological Office and Department of Civil Protection and Emergency Management which were used to monitor volcanic plume height and fire fountain height. A number of different camera designs optimised for different power and communications constraints were used, some built in house at IMO, and they will be presented here. To make a 3D height measurement from a 2D web camera image requires extra geometric constraints, which are provided by assuming the vent location and wind direction, in a similar manner to the method applied at Etna. We have implemented this technique as a react.js single page app, which is kept updated by a messaging queue system which pushes new images through the servers at IMO. Additionally, the webcameras have to be calibrated, in that the geometry of the camera and lens distortion parameters have to be known - this is either perfomed in the laboratory, or where the cameras were not available before installation, using one of a number of vicarious calibration techniques developed for this purpose. The resulting plume heights were used to constrain SO2 dispersion models that were the basis for air quality forecasts during the eruption. 
New luminescence chronological tools for dating and tracing sediment movement
Authors: Rhodes Ed , Ivester Andrew , Dolan James , Gauriau Judith , Van Dissen Russ , Little Tim
Published: March 2022

As part of a large research project reconstructing fault slip rates, palaeoseismiology and landscape evolution in New Zealand, we have developed a range of new chronological tools with applications to sediment. These closely related methods are based on Infra-Red Stimulated Luminescence (IRSL) signals of alkali feldspar, and allow us to determine aspects of transport and burial at the scale of individual grains over time periods ranging from 1 to 300,000 years. In particular, we have introduced and tested a method referred to as 3ET-IRSL (Three Elevated Temperature IRSL), and we are also applying a MET-IRSL (Multiple Elevated Temperature IRSL) approach comprising measurement sequences that include five IRSL measurements at different temperatures. These techniques can be used in different ways to filter complex single grain IRSL apparent age distributions that arise from processes including short duration reworking associated with incomplete trapped charge removal during transport. These methods were primarily designed to improve chronological control for sediment dating in contexts where conventional approaches encounter significant challenges owing to the geomorphic setting including high volume, rapid deposition. However, these approaches can provide significant insight into the dynamics of sediment transport routes and rates at the individual grain scale. We will demonstrate the performance of these methods at key test sites, and assess the implications of our findings in New Zealand (NZ), coupling observations of relict fluvial terrace formation with landscape response to the Mw 7.8 Kaikoura earthquake of 2016. At one of our NZ sites, fluvial system response to this event is the opposite of that expected from the literature in terms of sediment deposition and erosion; the degree to which this represents a transient response is assessed. We highlight the amazing potential of these new tools for improving our understanding of source-to-sink sediment transport dynamics.
Micron-scale mechanical properties of soil aggregates amended with manure: experimental evidence and image-based finite element simulations
Authors: Qu Rong , Zhou Hu , Hallett Paul
Published: March 2022

Soil aggregates fracture through the coalescence of internal macropores (cracks), forming smaller fragments that change pore structure characteristics. Many studies have measured soil aggregate fracture with laboratory tests, but the impact of internal pore structure has remained elusive in the black box of soil.  This study, which is the first of its kind, uses Xray micro-CT imaging, mechanical measurement experiments and finite element simulations to investigate the relationship between soil pore-scale topology and aggregate mechanical properties including fracture energy. The soil aggregates came from a red soil (Acrisols) experimental field in Jiangxi, China that had been amended with different amounts of manure and lime. From Xray micro-CT, quantitative topology analysis extracted the pore network extraction method. Then the strain-stress relationship and fracture energy of the scanned aggregate were measured using a loading frame. The micro-CT images are used as geometry inputs to perform finite element methods to calculate effective Young’s modulus and detailed strain-stress distribution at micrometers. The experimental results showed that adding manure increased the elastic stiffness and fracture energy of the aggregate. The pore scale strain-stress distribution analysis from finite element simulations found these properties at aggregate scale were weakly correlated to bulk porosity but driven by the stress intensity distribution of the aggregates, agreeing with previous research on model soil structures.
Occurrence of low-level jets and multi-layer clouds over various urban agglomerations located in Indo-Gangetic Plain
Authors: Sharma Saloni , Mishra Amit Kumar
Published: March 2022

The continuous heat release over cities/urban areas during night owing to urban heat island effect causes turbulent mixing and sustained supply of moisture and cloud condensation nuclei to the boundary layer. This sustained supply of moisture helps in persistence of low-level clouds over these urban areas as compared to rural/suburban areas during night. The various dynamical process including cloud formation, transport and dispersion of moisture and pollutant at boundary level at night time is highly influenced by the nocturnal low-level jets .These nocturnal low-level jets are found to be stronger over urban . These low-level jets are associated with high vertical wind shear production which enhances the turbulent mixing below boundary layer and plays a critical role in formation of nocturnal stratus clouds. In this study we have identified the vertical location of low-level jets using radiosonde data.  We get two peak for the frequency of occurrence of low-level jets, first at around 500-1000 m (boundary-level jets) and another at 1500 m altitude for winter, pre-monsoon, monsoon and post-monsoon seasons. We have also shown the diurnal (morning and evening) variation in the low-level jet frequency for these four seasons. The measurements from radiosonde in this study are taken at 05:30 am Local time (00:00 UTC) and 5:30 pm (12:00 UTC). We have also identified the types of clouds classified on the basis of number of layers over the study areas and associated it with the occurrence of low-level jets.
Seasonal variations of seismic velocities in Greece measured from seismic noise cross-correlations
Authors: Delouche Estelle , Stehly Laurent , Campillo Michel
Published: March 2022

Greece is the most earthquake-prone country in Europe, as it is located at the intersection of the Eurasian and African plates, as well as at the western end of the North Anatolian fault zone.

The long term goal of this study is to monitor the spatio-temporal evolution of the mechanical properties of the crust around the Gulf of Corinth in Greece that is associated with seismic swarms and large magnitude (Mw>5) earthquakes. We found that the seismic velocity changes induced by tectonic processes in the upper crust in Greece are masked by the velocity variations associated with environmental factors such as seasonal changes of temperature and hydrological parameters. The aim of the present study is to quantify the seismic velocity changes in the upper crust that are due to these environmental parameters. To that end, we use 6 years (2015-2020) of continuous vertical noise recording in 142 stations and calculate daily auto-correlations. We use the stretching method to measure seismic wave velocity variations (dv/v) with a sliding window of 2 months in the [1-3]s period band corresponding to the shallow crust.  We find that in several regions, the seismic velocities exhibit strong seasonal variations in particular in karstic areas. We use data from 495 meteorological stations in order to assess if it is possible to model the observed seasonal variations of dv/v from temperature changes and rainfall. Preliminary results indicate that 1- the seasonal changes of temperature are unlikely to explain the seasonal changes of seismic velocities and 2- in several regions, the variations of the groundwater level induced by rainfalls can at least partially explain the observed velocity variations.

To complete this study, we turned to an analysis of GPS traces as an independent means of assessing modeled velocity variation and to analyze hydrologic processes within aquifers.
VAE4OBS: Denoising ocean bottom seismograms using variational autoencoders
Authors: Tsekhmistrenko Maria , Ferreira Ana , Hosseini Kasra , Kitching Thomas
Published: March 2022

Data from ocean-bottom seismometers (OBS) are inherently more challenging than their land counterpart because of their noisy environment. Primary and secondary microseismic noises corrupt the recorded time series. Additionally, anthropogenic (e.g., ships) and animal noise (e.g., Whales) contribute to a complex noise that can make it challenging to use traditional filtering methods (e.g., broadband or Gabor filters) to clean and extract information from these seismograms. 

OBS deployments are laborious, expensive, and time-consuming. The data of these deployments are crucial in investigating and covering the "blind spots" where there is a lack of station coverage. It, therefore, becomes vital to remove the noise and retrieve earthquake signals recorded on these seismograms.

We propose analysing and processing such unique and challenging data with Machine Learning (ML), particularly Deep Learning (DL) techniques, where conventional methods fail. We present a variational autoencoder (VAE) architecture to denoise seismic waveforms with the aim to extract more information than previously possible. We argue that, compared to other fields, seismology is well-posed to use ML and DL techniques thanks to massive datasets recorded by seismograms. 

In the first step, we use synthetic seismograms (generated with Instaseis) and white noise to train a deep neural network. We vary the signal-to-noise ratio during training. Such synthetic datasets have two advantages. First, we know the signal and noise (as we have injected the noise ourselves). Second, we can generate large training and validation datasets, one of the prerequisites for high-quality DL models.

Next, we increased the complexity of input data by adding real noise sampled from land and OBS to the synthetic seismograms. Finally, we apply the trained model to real OBS data recorded during the RHUM-RUM experiment.

We present the workflow, the neural network architecture, our training strategy, and the usefulness of our trained models compared to traditional methods.
Bryophyte-lichens dominated biological soil crusts affect soils and ecohydrology in temperate forests in Germany
Authors: Seitz Steffen , Veste Maik
Published: March 2022

Forest dieback can be both a consequence and a cause of climate change. The changing climate does not only lead to temperature increases but also changes in the precipitation regime. Extreme events have increased sharply in recent years, making drought and heat waves ubiquitous. Meanwhile, for temperate forests, drought stress is considered one of the most serious impacts of climate change. In this context, forest soils are of great importance in their hydrological functions, as well as their feedbacks with ground vegetation. In this context, biological soil crusts are key drivers of functional processes and ecosystem development, also under forest, where they have been less studied so far. Bryophyte and lichen dominated communities can importantly affect e.g. water storage and discharge as well as soil development and stabilization. Moreover, they contribute to carbon and nitrogen cycling and play an important role in biogeochemical processes. Their species composition depends on soil properties such as texture and pH, on microclimate and as poikilohydric plants, their ecophysiology is strongly dependent on water availability, differing in time and space.

For a better understanding of ecohydrological and soil stabilizing functions of biological soil crusts within forest ecosystems, their spatial and temporal activity needs to be linked with microclimate and monitored continuously in the field. Therefore, we investigate the microclimatic conditions and activity of bryophyte-lichen-dominated biological soil crusts on sandy soils in Linde, Brandenburg and silty-clayey soils in the Schönbuch Nature Park, Baden-Württemberg, Germany. Water regimes within mosses and substrates are continuously determined with a novel biocrust wetness probe (BWP). Moreover, the interactions between mosses and soils are investigated in infiltration boxes with cultivated moss species. It could be shown so far, that moss-dominated biological soil crusts decrease infiltration and soil water availability in the dry sandy soils in Brandenburg and further comparative investigations will now be processed. We thus contribute to the study of effects of bryophyte-lichen communities on soil water retention, soil structure, with a focus on drought resistance of forest stands, as well as soil development at disturbance sites in temperate forest ecosystems.
A fully-open approach to modeling TC storm surge on a global scale
Authors: Vogt Thomas , Treu Simon , Mengel Matthias , Frieler Katja , Otto Christian
Published: March 2022

The existing research about hindcasting flood surges and flood plains caused by tropical cyclones (TCs) is largely specific to single storms, regions or countries. Often enough, the tools and data used are not publicly available, making it challenging to extend those analyses to other world regions. For instance, there is not yet a global data set of flood surges and flood extent maps from tropical cyclones. 

We present a modeling framework for hindcasting TC surges, based on the open-source software GeoClaw. We use open-source software and publicly available data sources only, making our approach fully transparent, reproducible and reusable for a global community of impact and risk modelers. The selected input data products include all world regions. Thus, our setup can be applied to all ocean basins that experience TCs. We evaluate our framework by comparing i) the flood surges of selected events to tide gauge records and modeled (GTSM) sea level, and ii) the flood extent maps to a global data set of satellite-based (MODIS) flood maps for the period 2000-2019.

Our analysis of tide gauge records shows that the setup captures the storm surge component of ocean dynamics at gauge locations very well, even though the model's capability to incorporate astronomical tides is limited. From the satellite-based flood maps, it becomes clear that beneath storm surge also rainfall and fluvial floods are important drivers of TC-related flooding, making it difficult to evaluate our model's performance based on its agreement with observed flood extents. Further, a comparison with high water marks in the field indicates that satellite-based products are often not sufficient to capture the full extent of short-term coastal flooding due to limited satellite overpass times. In this sense, storm surge model output can complement satellite observations.

The modeling framework allows us to generate globally consistent TC storm surge hazard data for all world regions, including the global south and least developed countries. It is suitable for historical analyses as well as for attribution studies or future climate projections, based on synthetic events or ensembles.
AI-based blending of conventional nowcasting with a convection-permitting NWP model
Authors: Kann Alexander , Atencia Aitor , Scheffknecht Phillip , Giannakos Apostolos
Published: March 2022

For hydrological runoff simulations in hydropower applications, accurate analyses and short-term forecasts of precipitation are of utmost importance. Traditionally, radar-based extrapolations are used for very short-term time scales (approx. 0 - 2 hours ahead). However, during recent years, convection-permitting NWP models have become better at very high spatial and temporal resolution forecasts (e.g. through radar assimilation, RUC configurations). Such models have the advantage of capturing the complex and non-linear evolution of precipitation systems like fronts or thunderstorms in a more physically accurate way than extrapolations, but they are also prone to inaccuracies in precipitation distribution. The aim of this paper is to employ machine learning to combine the strengths of the conventional radar extrapolation (localization and movement of existing storms) with the benefit of the model’s ability to predict storm evolution.  Results show that even a relatively simple sequential deep neural network is able to outperform both, the operational nowcasting and NWP model forecasts. However, the results are highly sensitive to variable selection, loss function, and localization features have a large impact on performance, which is also discussed.
Earth's free-oscillation spectrum as a tool to assess mantle circulation models
Authors: Schuberth Bernhard , Strutz Dominik , Schneider Anna
Published: March 2022

Geodynamic inverse models that aim at retrodicting past mantle evolution require accurate estimates of its thermodynamic present-day state. Tomographic models are in principle well suited to provide this information. However, a fundamental problem that impacts the quality of the retrodiction arises from their inherently limited resolving power and the fact that the magnitudes of seismic heterogeneity are difficult to constrain owing to the necessity to regularize the inversions (e.g. by norm damping). To get a better understanding of the magnitudes of heterogeneity in the mantle, one option is to predict seismic velocity variations from the temperature field of forward mantle circulation models (MCMs) in combination with thermodynamic models of mantle mineralogy.  Temperature is not a free parameter in these models, but rather constrained by the underlying conservation equations and relevant input parameters. If the geodynamic models are run at earth-like Rayleigh number, temperature variations are expected to feature realistic magnitudes, which, together with the mineralogical mapping, should lead to realistic magnitudes of seismic heterogeneity. This has been investigated in previous studies by computing secondary predictions for the MCMs, such as seismic body wave traveltimes and geoid undulations. A complicating factor, however, is the trade-off between thermal and compositional variations that both may affect the seismic velocities. A further complexity arises from the fact that the elastic velocities of the mineralogical model need to be corrected for the effects of anelasticity, the parameters of which are poorly known.  Thus, a range of seismic velocity values may still be possible for a given temperature. 

Here, we explore the possibility to use Earth's normal mode spectrum to narrow the range of plausible magnitudes of seismic heterogeneity in the mantle. To this end, we compute free-oscillation spectra with full coupling of modes below 3.5 mHz in our geodynamic models.  In our analysis, we consider different measures to investigate whether the normal mode data may provide complementary information to earlier assessments of MCMs based on body waves. In addition to the direct misfit between spectra of real and synthetic data, the variance of a large number of stacked multiplets can be used to constrain the even degree covariance of lateral heterogeneity under certain assumptions. Using different realizations of seismic MCM structure that differ in terms of the anelastic temperature to velocity mapping, we will analyse the potential of normal mode data to put tighter constraints on the magnitudes of heterogeneity.
A regional flood impact prediction tool using machine learning to manage flood risk in real-time. A case study in New Zealand.
Authors: Mourot Phil , Lim Nick , Pfahringer Bernhard , Bifet Albert
Published: March 2022

Regional resilience has been identified as a key strategic priority for the Waikato Regional Council in New Zealand. Weather extremes are going to impact more our communities and what is important is how the regions can anticipate and respond to the impact of climate change. Flooding is the Waikato region’s most frequent and widespread natural hazard. The council’s priority is to prevent risks to people and property by providing flood protection and flood warnings. The local government works close to emergency services and civil defence to help people at risk. In addition to flood defences, flood impact prediction can help our communities be more resilient. This research is part of the TAIAO project (taiao.ai) that aims to develop new machine learning (ML) methods to provide a robust and fit-for-purpose tool to help New Zealand solve critical environmental problems. Over the past decade, increased research has aimed to develop new hydrological models for flood forecasting using machine learning. A data-driven approach provides the ability to deliver reliable results, especially for short-term forecasts, without the complete and complex knowledge of the physical processes usually required by a physically-based approach. Our research focuses on developing a regional real-time flood forecasting tool for emergency management that can run with low computational effort and a small number of parameters. Our target is to provide a better flood prediction with available information from the observation network. For our pilot study, we focus on the Coromandel Peninsula, a popular destination for the holidays, and where the weather is often challenging to forecast, like in New Zealand in general. We have used and compared the capability of various ML models to provide accurate results with low timing errors. To solve the problem of lagged prediction, we have developed a more holistic approach that combines hydrological state parameters and Long Short-Term Memory networks (LSTM). From these preliminary results, we demonstrate the real challenge to embed our LSTM-based model into operational procedures to predict with a lead time from 1 hour to 6 hours the severity of the impacts of heavy rainfall. The predictions are presented in a helpful way that facilitates decision-making and improves the regional flood response management.
The initiation mechanism of the bag-breakup fragmentation and scaling of sea spray at high winds
Authors: Troitskaya Yuliya , Kandaurov Alexander , Sergeev Daniil
Published: March 2022

The "bag breakup" fragmentation is the dominant mechanism for generating spray in hurricane winds, which parameters substantially affect the exchange processes between the ocean and the atmosphere and, thereby, the dynamics of the development of sea storms. This fast process can only be studied in the lab using sophisticated experimental techniques based on high-speed video filming. In such circumstances, the transfer of laboratory data to field conditions requires a kind of theoretical model that describes how the initiation of disturbances occurs, which then lead to fragmentation events, what is the threshold for the fragmentation, what is the volume of liquid, which determines the size of spray droplets, that undergoes fragmentation, and how it depends on wind parameters, etc. The conclusions of the model can be first verified in the laboratory experiment and then applied to field conditions.

 

In the present work, such a model is proposed. First of all, a linear theory of small-scale disturbances on the water surface under the action of a strong wind has been built, which makes it possible to describe their structure, dispersion properties and determine the threshold value of the dynamic airflow velocity at which such disturbances become growing. These disturbances comprise small-scale ripples concentrated within the thin surface layer and growing fast due to shear instability of the wind drift flow in the water. The peculiarity of the structure of these disturbances enables one to consider the nonlinear stage of their evolution within the Riemann simple wave equation modified to describe the increasing disturbances. The analytical solution of the obtained equation suggests the scaling of the volume of liquid undergoing the "bag-breakup" fragmentation, to estimate the scale of the formed droplets and the speed of their injection into the atmosphere. The scaling correctly describes the dependencies of these quantities on the wind friction velocity obtained in laboratory experiments.

 

The obtained results are applied for the construction of the fetch-dependent spray generation function, which is applicable in the field. Within the Lagrangian stochastic model for the inertial droplets in the marine boundary layer, the momentum, heat, moisture, and enthalpy exchange coefficients are calculated. One should notice a substantial feedback effect on the atmosphere caused by the presence of spray in hurricane conditions.

This work was supported by RFBR grant 19-05-00249 and RSF grant 19-17-00209.

 
Extreme Value Analysis of Madden-Julian Oscillation Events
Authors: Minjares Mónica , Yiou Pascal , Serra Isabel , Barreiro Marcelo , Corral Álvaro
Published: March 2022

The Madden-Julian Oscilation (MJO) is an eastward equatorially propagating mode with a strong influence on the precipitation in the tropics on sub-seasonal timescales. Although, several studies have widely analysed the MJO, its activation and evolution are not fully understood [1].

The purpose of this study is to analyse the statistical features of the most intense MJO events.

We perform the study using two different indices describing the MJO: The popular Wheeler and Hendon index (1979-2021), based on the first two principal components of a multivariate empirical orthogonal function analysis of a combination of outgoing longwave radiation (OLR) and 200 mb and 850 mb zonal winds, as well as the Oliver and Thompson index (1905-2015) based on surface pressures [2].

In this study an event takes place when the index amplitude exceeds a threshold for a certain number of days. With this, we define the observables of an event; these are, the maximum amplitude, duration and size, which is the sum of the amplitudes along the duration of an event.

We use extreme-value theory to fit the generalized Pareto distribution (GPD) to the different distributions of observables and we compare the results with the fitting of a simple power-law tail and other heavy-tailed distributions. We also compare the performance of several advanced extreme-value-statistics tools to find the threshold over which the GPD holds.

 

1.Kiladis, G. N., Dias, J., Straub, K. H., Wheeler, M. C., Tulich, S. N., Kikuchi, K., ... & Ventrice, M. J. (2014). A comparison of OLR and circulation-based indices for tracking the MJO. Monthly Weather Review, 142(5), 1697-1715.

2.Klotzbach, P. J., and E. C. J. Oliver (2015), Variations in global tropical cyclone activity and the Madden-Julian Oscillation since the midtwentieth century, Geophys. Res. Lett., 42, 4199–4207.
Exploring the potential of cosmic muon scattering to measure the snow water equivalent
Authors: Orio Aitor , Alonso Esteban , Martínez Pablo , Díez Carlos , Gómez Pablo
Published: March 2022

The seasonal snowpack influences the hydrology, ecology and economy of the areas where it is present. However, the real time monitoring of the seasonal snowpack is a still well known scientific challenge. In this study, we have explored the potential of muon scattering radiography (MSR) to infer the snow water equivalent (SWE) of the snowpack. We have used the energy and mass balance model Snowpack to realistically simulate the time evolution and microstructure of the snowpack. The ERA5-Land reanalysis was used as forcing of Snowpack, in a location close to the Monte Perdido massif (Central, Pyrenees) at an elevation of 2041m above sea level. The simulations cover the hydrologic year 2015/2016, approximately reaching up to 700mm of peak SWE. Then, we have coupled the Snowpack numerical simulations with the Geant4 model to simulate the propagation of the muons through the snow layers and to collect the deviation of the muon trajectories. We have measured these deviations with a virtual muon detector based in multiwire proportional chambers, replicating a real detection system designed by us. The obtained distributions of muon deviations have exhibited a strong correlation with the simulated SWE, showing a coefficient of determination of 0.99. This model presents a root-mean-square error (RMSE) of 23.9mm in the SWE estimation. In order to validate the simulation analysis results, we have replicated the numerical experiments under controlled conditions, measuring three artificial snow samples ranging from 0 to 200 mm of SWE in our laboratory. We have measured the samples with an experimental setup composed of the real muon detector whose hardware was virtually replicated for the numerical experiments. Then, we have applied the model derived from the numerical simulations to the muon deviations measured in our laboratory. We have calibrated the real measurements and we have obtained a RMSE of 38.4mm in the SWE estimation. These results show that MSR is a promising non-destructive technique that can be used for the deployment of accurate SWE monitoring networks and can eventually provide information from the internal layered structure of the snowpack.
Upper Pleistocene dust dynamics reconstructed by isotope fingerprinting and the magnetic fabric of Loess-Palaeosol-Sequences 
Authors: Vinnepand Mathias , Fischer Peter , Craig Carol-Ann , Hambach Ulrich , Zeeden Christian , Thornton Barry , Tütken Thomas , Jöris Olaf , Prud'homme Charlotte , Schulte Philipp , Moine Olivier , Fitzsimmons Kathryn , Lehmkuhl Frank , Schirmer Wolfgang , Vött Andreas
Published: March 2022

Loess-Palaeosol-Sequences (LPS) are the most widespread aeolian sedimentary deposits providing climatic- and environmental records across continents. As dust sinks, they may archive information on dust source dynamics, if targeted source signals survived processes operating during production, transport, and syn- and post-depositional alteration of particles and sediments. Yet, our knowledge about such dynamics through palaeoenvironmental changes during the Upper Pleistocene remains vague. This limits our understanding of thresholds that may have (de-) activated dust sources causing major environmental changes in prevalent areas. We thus combine results of isotope- (87/86Sr, 143/144Nd) and major element (Si/Al) provenance proxies that react differently to pre-, syn- and post depositional alteration processes, with granulometry (U-ratio) and the anisotropy of magnetic susceptibility (AMS). Granulometry is recognised as an indicator for wind strengths and the primary magnetic fabric of loess deposits has been successfully used to reconstruct surface near wind directions. We apply our approach on the RP1 profile of the Schwalbenberg LPS that covers the late OIS 3 and the OIS 2 in centennial-scale resolution. The site is embedded in the Middle Rhine Valley (Germany) dividing the Rhenish Massif in its western and eastern part. Consequently, the Schwalbenberg seems appropriate to trace provenance shifts as it is linked to a distal dust source via the Rhine and as it is surrounded by potential local dust sources of the Rhenish Massif. Our results indicate shifts in source areas NNE-SSW off the site, contemporary with increasing frost dynamics and aridification. Both factors seem to enhance dust inputs from the Rhine system up to a threshold where the Rhenish Massif gets activated as a dominant source. Geochemical fingerprinting and AMS at the Schwalbenberg RP1 LPS reveal insights into dust source dynamics that allow for estimating their emission potential during Upper Pleistocene palaeoenvironmental changes.  