bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic Event Characterization using Manifold Learning Methods
Authors: Bregman Yuri , Ben Horin Yochai , Radzyner Yael , Niv Itay , Kahlon Maayan , Rabin Neta
Published: March 2022

Manifold learning is a branch of machine learning that focuses on compactly representing complex data-sets based on their fundamental intrinsic parameters. One such method is diffusion maps, which reduces the dimension of the data while preserving its geometric structure. In this work, diffusion maps are applied to several seismic event characterization tasks. The first task is automatic earthquake-explosion discrimination, which is an essential component of nuclear test monitoring. We also use this technique to automatically identify mine explosions and aftershocks following large earthquakes. Identification of such events helps to lighten the analysts’ burden and allow for timely production of reviewed seismic bulletins.

The proposed methods begin with a pre-processing stage in which a time–frequency representation is extracted from each seismogram while capturing common properties of seismic events and overcoming magnitude differences. Then, diffusion maps are used in order to construct a low-dimensional model of the original data. In this new low-dimensional space, classification analysis is carried out.

The algorithm’s discrimination performance is demonstrated on several seismic data sets. For instance, using the seismograms from EIL station, we identify arrivals that were caused by explosions at the nearby Eshidiya mine in Jordan. The model provides a visualization of the data, organized by its intrinsic factors. Thus, along with the discrimination results, we provide a compact organization of the data that characterizes the activity patterns in the mine.

Our results demonstrate the potential and strength of the manifold learning based approach, which may be suitable to other in other geophysics domains.
Dynamical Downscaling and Data Assimilation: Insights from the Case Study of the "Year Without a Summer" 1816
Authors: Pfister Lucas , Stucki Peter , Martynov Andrey , Brönnimann Stefan
Published: March 2022

One year after the eruption of the Tambora volcano, the “Year Without a Summer” of 1816 was characterised by extraordinarily cold periods in (Central) Europe, and it was associated with severe crop failures, food shortages, famine and socio-economic disruptions.

The summer of 1816, has been analysed based on a number of early meteorological measurements, as well as on ample documentary information. A statistical reconstruction of spatial fields with daily resolution has been conducted for Switzerland. However, this dataset encompasses only a limited set of variables. In turn, dynamical downscaling methods allow to reconstruct past weather on a higher temporal and spatial resolution. In our work, we simulate a particularly cold episode in June 1816 by downscaling data from the Twentieth Century Reanalysis version 3 (20CRv3). The simulation uses the Weather Research and Forecasting (WRF) model with three nested domains for the greater Alpine region and provides hourly output with a 3-km resolution. In addition, we include recently digitised station series of temperature and pressure for a Three-Dimensional Variational (3DVAR) data assimilation in the innermost domain. Results are then validated against independent station observations.

First results suggest that dynamical downscaling and data assimilation may become a promising approach to obtain physically consistent information on past weather on a local and subdaily scale. This may hold even for extreme events in an era with a scarce network of instrumental weather observations compared to today, although erroneous results may occur. A successful application of dynamical downscaling and data assimilation for the early 19th century might open the door for a regional atmospheric reanalysis product that covers the last two centuries.
Charcoal morphologies to discriminate fuel source and fire temperatures 
Authors: Feurdean Angelica , Tintner Johannes
Published: March 2022

Wildfires can have major impacts on terrestrial ecosystems and climate. The analysis of charcoal fragments in peat and lake sediments is the most widely used approach to reconstruct past biomass burning and fire regimes. This method typically relies on the quantification of the total charcoal content of the sediment. However, there is an increasing effort to use morphologies (finer anatomical features) and morphometrics (length: width ratio) of charcoal particles to advance our understanding of fuel burnt and fire types. We used experimental burnings in the laboratory for plant species from boreal Siberia, which are also commonly found in the Northern Hemisphere, to expand the reference datasets on morphological distinctions between species or fuel types. We also tested the effect of burning temperature (five temperature categories ranging from 250 to 450 °C) on char mass and morphometrics of charred plant material. We found that graminoid charcoal particles are most elongate (6.7-11.5), leaves are the shortest and bulkiest (2.1-3.5) while twigs and wood are intermediate (2.0-5.2). Our findings correspond well to the few existing comparable experimental measurements. Further, the use of fine charcoal features was successful in separating wood, graminoids, and leaves, but it was difficult to further differentiate these fuel types i.e., leaves and wood from trees and shrubs, due to overlapping features. In terms of charred mass, graminoids, Sphagnum, and wood (trunk) lose the most mass at low burn temperatures (<300°C), whereas heathland shrub leaves, brown moss, and ferns at high burn temperatures. Ongoing work applying micro-Fourier Transformed Infrared Spectroscopy (FTIR) on both modern charred particles produced at different temperature ranges and fossil charcoal will help estimate the pyrolysis temperature and fuel type. Similarly, our focus is to expand reference datasets on charcoal morphologies and FTIR to other major biomes, particularly grasslands. We also highlight the further investigations into charcoal experimental studies needed to refine the histories of past wildfires.
​Development of ice sublimation device for analyses of methane isotopes in ice with high impurities
Authors: Dyonisius Michael , Döring Michael , Blunier Thomas
Published: March 2022

Common methods to liberate the air bubbles trapped in ice cores include melting (wet extraction) and mechanical destruction (dry extraction) of ice under vacuum. Wet extraction is commonly used for CH4 analyses; however, a recent study (Lee et al., 2020) showed that the presence of liquid water can introduce extraneous (non-paleoatmospheric) CH4 from the reaction between the meltwater and impurities. Measurements of CH4 using dry extraction methods had previously been done (e.g., Ferretti et al., 2005); however, a laboratory intercomparison study showed that dry extraction system generally have higher blanks (Sowers et al., 1997) for CH4. It is hypothesized that friction between components (either metal with metal or metal with ice) can be a source of contamination (e.g., Nicewonger et al., 2016; Sowers et al., 1997). A third method to liberate air trapped in ice core bubbles is sublimation under vacuum (e.g., Wilson and Donahue, 1989; Schmitt et al., 2011). The sublimation method guarantees complete gas extraction from both the air bubbles and the ice matrix / clathrates (Bereiter et al., 2015), and should be free of problems associated with wet extraction. Here we present a new sublimation system that aims to sublimate ~250g of ice and extract ~25 mL STP of air for measuring CH4 isotopes in ice with high impurities. We use three high powered (500W each) infrared lamps that emit peak radiation at wavelength of 1500 nm, which coincides with a local maxima in ice absorption spectra (Warren and Brandt, 2008). To ensure even sublimation, the infrared lamps are attached to a custom-made mounting bracket that is rotated around the glass vessel. This system is coupled to a previously built Gas Chromatography Isotope Ratio Mass Spectrometry (GC-IRMS) system (Sperlich et al., 2013) to purify and analyze δ13CH4 isotopes. At the time of writing, the GC-IRMS system is able to achieve 0.06 ‰ precision on standard air injections with contemporary CH4 mole fraction (1850 nmol/mol). Further testing to characterize the performance of the system using blank ice and test ice of known mole fraction and isotope values is underway.
Compositional two-phase flow and phase behavior in nanoporous media: pore-level physics, pore-network modeling, and upscaling
Authors: Chen Sidian , Jiang Jiamin , Guo Bo
Published: March 2022

Multiphase fluid flow and multicomponent transport in porous media are often controlled by thermodynamic phase change dynamics. In a nanometer-scale pore space, the phase behavior of a multicomponent fluid deviates from that in a larger pore space (i.e., micrometer or greater)—the pressure and temperature at which the fluid begins to evaporate or condensate in nanopores can significantly differ from those in large pores. This pore size-dependent phase change behavior is further complicated in natural nanoporous media (e.g., clay soil or shale rock) that often contain a significant fraction of interconnected pores spanning from nanometers to micrometers. While the nanoconfined phase behavior in a single nanopore has been extensively studied by molecular-level theories, the new molecular-level understanding has not yet been incorporated in Darcy-scale continuum models.

We address this challenge of scale translation by developing a new pore-network-scale modeling framework for flow, transport, and thermodynamics in nanoporous media. The new modeling framework is comprised of 1) a phase-equilibrium model that accounts for the pore-size and -geometry dependent nanoconfinement effects and 2) a fully implicit dynamic pore-network model framework coupling the individual-pore nanoconfined phase-equilibrium model with the two-phase compositional flow. This framework for the first time allows us to investigate the interactions between compositional flow dynamics and nanoconfined phase behaviors at an REV-scale, which we will illustrate by a series of numerical experiments on complex networks with pores varying in size, geometry, and wettability.
Forest soil and deadwood CH4 fluxes in response to climate change and forest management
Authors: Johannesson Carl-Fredrik , Larsen Klaus Steenberg , Nordén Jenni
Published: March 2022

Methane (CH4) is the second largest contributor to global warming and the importance of reducing CH4 emissions was recently highlighted through the Global Methane Pledge launched in 2021. Forest soils can act both as sinks and sources of CH4, largely depending on the hydrological status of the soil, and both direction and magnitude of CH4 fluxes often vary considerably even across small spatial and temporal scales. Thus, projected changes in precipitation patterns can be expected to affect both total CH4 budgets and the spatiotemporal distribution of sinks and sources. Forest management – for example clear cutting and nitrogen (N) fertilization – also affects CH4 cycling in forests with the potential to turn CH4 sinks into CH4 sources, but little is currently known about the mechanisms and to what extent fluxes are affected by forest management.

In the ForBioFunCtioN project, we have set up an extensive climate and management manipulation experiment across five Norwegian spruce dominated bilberry forest sites spanning from a recent clear-cut to mature managed (80 years) and old unmanaged (140 years) stands. Treatments include warming with open-top chambers, simulated increased precipitation and additions of N fertilizer and biochar in a total of 12 different treatment combinations (n = 144). We utilize state-of-the-art technology (LI-7810 Trace Gas Analyzer, LI-COR®) for measurements of soil-atmosphere and deadwood-atmosphere exchange of CO2 and CH4.

Here, we present the experimental setup and soil and deadwood flux measurements of CO2 and CH4 from June to December 2021. Initial results show that soil CH4 fluxes vary considerably both between and within sites yet indicate short-term responses of CH4 fluxes to addition of biochar and N fertilizer in particular.
Arctic Mid-Ocean Ridge seismicity: Results from an OBS deployment at Loki’s Castle 
Authors: Lien Marie Eide , Pilot Matthias , Schlindwein Vera , Ottemöller Lars , Barreyre Thibaut
Published: March 2022

Activity along the Arctic Mid-Ocean Ridge (AMOR) has been progressively explored over the past 20 years. Along the ridge, processes such as dike intrusion and faulting cause earthquakes. We focus on an area around the Loki’s castle hydrothermal vent field (LCVF), located on the Mohn ultra-slow spreading ridge. Ultra-slow spreading systems are strongly controlled by tectonic processes, which provide an opportunity to study almost exclusively the effect of tectonism on a hydrothermal vent field.

In June 2019, we deployed a network of eight broadband ocean bottom seismometers (OBS) in an area of about 20 by 20 km around the LCVF. The OBSs were deployed for a one-year monitoring period until July 2020. We processed the OBS data using an automatic detection routine and machine learning approach to pick phases, and then located the local earthquakes based on a 1D velocity model. This provided an earthquake catalogue that was interpreted to understand the seismicity in terms of spatial and temporal distribution, and to identify fault structures. Within the broader tectonic system we aim to enhance our understanding of the LCVF.
Interplay between magnetic reconnection and flapping instabilities in the magnetotail: global hybrid-Vlasov simulation of the Earth’s magnetosphere
Authors: Cozzani Giulia , Ganse Urs , Pfau-Kempf Yann , Alho Markku , Suni Jonas , Grandin Maxime , Turc Lucile , Zaitsev Ivan , Bussov Maarja , Dubart Maxime , George Harriet , Horaites Konstantinos , Manglayev Talgat , Papadakis Konstantinos , Tarvus Vertti , Zhou Honyang , Palmroth Minna
Published: March 2022

Magnetic reconnection is a fundamental process in plasma and a major cause of energy conversion and transport by means of magnetic field topology reconfiguration. It takes place in thin plasma sheets, where energy is often explosively converted from the magnetic field to plasma heating and particle energization. Magnetic reconnection in Earth’s magnetotail is thought to play a crucial role in geomagnetic storms and substorms, one of the most explosive phenomena in the context of Earth’s magnetosphere. Several other current sheet-related processes, such as the ballooning instability, tearing instability, and a variety of flapping instabilities, can occur in the magnetotail, and the interplay between magnetic reconnection and these current sheet instabilities is largely unexplored. In this study, we investigate the interplay between magnetic reconnection and other instabilities taking place in the magnetotail current sheet, using a hybrid-Vlasov simulation that provides a three-dimensional description of the global coupled solar wind-magnetosphere system down to the ion-kinetic scale. In particular, we identify and characterize the flapping instability that develops in the magnetotail midnight sector and we discuss its dynamics in relation to magnetotail magnetic reconnection.
Insights into circumglobal Rossby wave patterns from space/time spectral analysis
Authors: D'Andrea Fabio , Riboldi Jacopo , Rousi Efi , Lott Francois , Riviere Gwendal
Published: March 2022

Circumglobal Rossby wave patterns (CRWPs) are large-scale configuration characterized by amplified Rossby waves stretching in the zonal direction across a broad portion of a latitude circle. Previous research considered CRWPs mainly from two points of view: either as particular type of planetary wave, undergoing quasi-resonant amplification when trapped between two turning latitudes, or as a single Rossby wave packet (RWP) being ducted zonally in presence of particularly strong meridional potential vorticity gradient, that acts as a waveguide. Although with different characteristics, a structured waveguide for Rossby waves is needed in both cases.

Space/time spectral analysis allows to study CRWPs from their spectral projection over a range of wavenumber/phase speed harmonics, with the implicit assumption that a CRWP would project only over few zonal wavenumbers and propagation speeds characterizing it over a broad portion of the hemisphere. Such spectra are calculated from meridional wind at 250hPa over a sliding time window of 61d, in order to consider the intraseasonal variability in spectral power. The application of principal component analysis to this data set allows for few leading variability modes in the spectral domain during boreal winter, and these modes appear to be related to CRWPs.

They correspond to the baroclinic propagation of amplified RWPs from the Pacific to the Atlantic storm track in a hemispheric flow configuration displaying enhanced meridional gradients of geopotential height over midlatitudes. The first CRWP is forced by tropical convection anomalies over the Indian Ocean and features the propagation of amplified Rossby wave packets over northern midlatitudes, while the second one propagates rapidly over latitudes between 35◦N and 55◦N and appears to have extratropical origin. An anomalous equatorward propagation of Rossby waves from the Atlantic eddy-driven jet to the North African subtropical jet is observed for both CRWPs These results support the perspective that CRWPs are substantially related with the circumglobal propagation of RWPs.
How does the weather affect the response of porous hose wind noise reduction systems?
Authors: Assink Jelle , Evers Läslo
Published: March 2022

In order to reduce the observation of wind and turbulence on infrasound sensors, wind noise reduction filters are in place at most infrasound stations. The use of such filters is essential to obtain low background noise levels, which in turn facilitates detection of low signal-to-noise (SNR) infrasound signals. Most filters operate by spatially integrating the pressure field in the vicinity of an infrasound sensor. While the turbulent pressure (partially) de-correlates over the spatial length scale of the filter, the infrasound wave remains coherent. Infrasound arrays that are part of the International Monitoring System make use of advanced pipe array structures that have been designed for long-term deployments. The response is of these systems is stable and well understood. In contrast, many experimental infrasound arrays have relied on the use of porous hoses for wind noise reduction. Porous hoses appear to be efficient, yet cost-effective solutions for short term deployments. Over longer timescales, however, it is known that the response of the hoses can vary significantly and that the hoses can degrade over time.

 

In this work, we investigate the varying response of the porous hoses at the De Bilt Infrasound Array in the Netherlands, using a reference infrasound sensor without hoses. Since a weather station is co-located with the infrasound array, this allows us to study the relationship between the response of the hoses and various meteorological parameters. It is found that under dry conditions, the hoses act as a low-pass filter with a corner frequency around 1.8 Hz, which is consistent with earlier work. We shows that the higher frequency signals with sufficient SNR can be reasonably well reconstructed after a deconvolution step. Under wet conditions however, the hoses become highly absorptive. This can affect observations down to 0.1 Hz. The excess attenuation can be attributed to the presence of rain and/or dew. Although these effects appear to be reversible to some degree, this work shows that care must be taken in the interpretation of data from infrasound arrays that make use of porous hoses.
Garnet U–Pb dating by LA–ICPMS: Opportunities, limitations, and applications
Authors: Millonig Leo J. , Beranoaguirre Aratz , Albert Richard , Marschall Horst , Baxter Ethan , Gerdes Axel
Published: March 2022

Geochronology provides the time frame for various fields of research in the earth sciences that investigate the geological history from the mineral scale to tectonic plates. The reconstruction of pressure–temperature-time (P–T–t) paths of metamorphic rocks from collisional settings such as orogenic belts, for example, is commonly achieved by linking chronological (U–Pb) and trace element data from U-rich accessory phases such as zircon, monazite, titanite, or rutile, with thermobarometric information derived from rock-forming minerals such as garnet. The ability to extract both types of information from one mineral makes garnet arguably the most versatile and powerful petrochronometer. Garnet has an extensive P–T stability field for a wide variety of rock compositions, and changes in P–T conditions during garnet growth are recorded in compositional changes. Garnet U–Pb ages can thus be linked to compositionally distinct garnet domains, providing a direct link between P–T estimates and chronological data. Although still in its infancy, U–Pb dating of metamorphic garnet by LA–ICPMS is an evolving petrochronological tool with a vast potential and a plethora of possible applications.

This contribution discusses the advantages and limitations of this method, as well as the significance and meaning of garnet ages. The benefits of the method, as compared to conventional isotope dilution techniques, are the ease of sample preparation, rapid data acquisition and processing, high spatial resolution, and relatively low costs. However, the very low (≤1-100 ng/g) and variable U content of regional metamorphic garnet and the frequently ubiquitous presence of inclusions of U-rich accessory minerals are obstacles that affect the precision and accuracy of garnet U–Pb dates, or may render a particular garnet sample undateable altogether. These various aspects of garnet U–Pb dating by LA–ICPMS will be examined by discussing metamorphic garnet from the Alps, which had previously been dated by Sm-Nd chronology (Pollington and Baxter, 2010).

Pollington, A.D., Baxter, E.F., 2010. High resolution Sm–Nd garnet geochronology reveals the uneven pace of tectonometamorphic processes. Earth and Planetary Science Letters 293, 63–71. https://doi.org/10.1016/j.epsl.2010.02.019
Insights from ACRUISE (Atmospheric Composition and Radiative forcing changes due to UN International Ship Emissions regulations) from aircraft, modelling, and satellite perspectives
Authors: Yang Mingxi , Bell Thomas , Bower Keith , Carslaw Ken , Choularton Thomas , Christensen Matt , Coe Hugh , Grosvenor Daniel , Lee James , Watson-Parris Duncan , Stier Philip , Yoshioka Masaru
Published: March 2022

Ship exhausts have historically been significant sources of sulfur dioxide and aerosols to the marine atmosphere and some global models suggest the emissions cause a large negative radiative forcing by modifying cloud properties. International Maritime Organisation (IMO, an agency of the UN) regulations require that ships in international waters reduce their sulfur emissions from a maximum of 3.5% to 0.5% from January 2020. The ACRUISE project, taking advantage of this unique large-scale aerosol perturbation, investigates the impacts of the IMO’s 2020 sulfur regulations on aerosols, clouds, and radiation in the North Atlantic and globally. Here I summarise our findings so far from intensive aircraft observations, high-resolution model simulations, and deep learning-based satellite cloud analysis. 

 

Aerosol-cloud interaction near shipping lanes was studied from an aircraft in the northeast Atlantic in 2019 as well as in 2021. Aerosol chemical and physical properties were markedly different between the two years, with much lower sulfur content, smaller, and less hygroscopic aerosols in 2021. A detailed analysis of the aerosol and cloud microphysics observations within/immediately outside the ship plumes will be performed to determine whether some clouds appeared to be strongly impacted by ship plumes, while other clouds were not. To help interpret the aircraft data and provide context, we ran nested regional domain simulations of the Met Office Unified Model for all flight campaigns. These high-resolution simulations (few hundred metres) show a generally diffuse pattern of perturbed trace gases and aerosols that are not apparent as individual ship tracks, suggesting that analysis of tracks alone may underestimate the climatic effects of ship emissions.

 

We have trained a deep learning model to detect ship-tracks in satellite imagery with good skill and applied it to the whole MODIS mission in order to develop a global climatology. We will discuss the spatial and temporal distribution of shiptracks relative to the underlying ship emissions, and particularly focus on the effects of the IMO regulation as well as the global COVID-19 pandemic. Ongoing work that combines airmass trajectory modelling with known positions of ships will enable us to assess the impact of ship emissions on all pixels, and not just those identified as ship tracks.
Large array of inselbergs and continuation of sub-Cambrian peneplain in the Baltic Basin based on interpretation of seismic data, Western Lithuania
Authors: Radzevicius Sigitas , Grendaitė Milda , Michelevičius Dainius
Published: March 2022

The sub-Cambrian peneplain is a well-known geological phenomenon in Scandinavia and it is found in sub-aerial outcrops in Finland, Sweden, and Norway. It is suggested that the peneplain formed within the Baltic Sea region in Cryogenian and Ediacaran / early Cambrian, when Baltica, a part of Rodinia at most of that time, experienced a tectonic stability, strong sheet-wash weathering and glaciations. While the peneplain outcrops at the surface in the Baltic Shield region, the remaining part of this peneplain is buried under the Phanerozoic sediments that comprise the Baltic Basin. This buried part of sub-Cambrian peneplain is known to have several inselbergs that occur as isolated ones or as sparse groups of inselbergs. From the results of interpretation of 2D and 3D onshore seismic data newly acquired in Western Lithuania, the continuation of sub-Cambrian peneplain was identified in Western Lithuania, a large array of inselbergs was mapped to the detail that the 3D seismic can permit, and the change in paleo-topography character of the Precambrian basement from flat to hilly and rough, was observed. The flat western side of our study area is interpreted as a continuation of the sub-Cambrian peneplain, which outcrops sub-aerially in Scandinavia while to the southeast it is buried under the strata of Baltic Basin. The southeastern part of our study area has many closely spaced hill-like features of various size, it is of considerable extent (at least 30 km) and does not comply with the peneplain’s definition on a local scale. It is interpreted as a part of large array of inselbergs. Though some of the largest palaeo-topography features in the study area were documented before, only the detailed mapping revealed that in Western Lithuania there is a large and dense array of inselbergs. This array of inselbergs is exceptional because it is the largest and densest of all known clusters of inselbergs in the Baltic Basin.
Control simulation experiment for a typhoon case with a global numerical weather prediction system
Authors: Terasaki Koji , Miyoshi Takemasa
Published: March 2022

The earth’s atmosphere is a nonlinear and chaotic system. A small difference in the initial condition makes forecast different due to the chaos, the characteristics known as the “butterfly effect”. The predictability has been improved by the development of the NWP model, data assimilation, and observations for a long time. However, severe weather such as typhoon and torrential rainfall is a threat for us. Weather modification has also been investigated, such as cloud seeding and rain enhancement. It distributes cloud condensation nuclei and enhances cloud formation based on the microphysical processes. Alternatively, this study explores to control a typhoon by taking advantage of the chaotic dynamics.

The Observing System Simulation Experiment (OSSE) is a widely used approach in data assimilation research. We extend the OSSE to what we call the control simulation experiment (CSE) which changes the nature state to the desired direction by adding control signals determined by the ensemble forecasts. This study targets a typhoon, which generated over the Northwest Pacific and hit Japan. We perform CSEs to weaken the typhoon, i.e., making the central sea level pressure (SLP) higher. We apply the control only to the horizontal wind field at the first model vertical layer. Here, we limit the control signal only to reduce the kinetic energy because it would be difficult to increase kinetic energy in a real-world intervention. The CSE is found effective, i.e., we successfully weaken the typhoon when it reaches Japan. We will present the most recent results at the meeting.
Reservoir inflow forecast by combining meteorological ensemble forecast, physical hydrological simulation and machine learning
Authors: Liu Junjiang , Yuan Xing
Published: March 2022

Accurate streamflow forecasts can provide guidance for reservoir managements, which can regulate river flows, manage water resources and mitigate flood damages. One popular way to forecast streamflow is to use bias-corrected meteorological forecasts to drive a calibrated hydrological model. But for cascade reservoirs, such approaches suffer significant deficiencies because of the difficulty to simulate reservoir operations by physical approach and the uncertainty of meteorological forecasts over small catchment. Another popular way is to forecast streamflow with machine learning method, which can fit a statistical model without inputs like reservoir operating rules. Thus, we integrate meteorological forecasts, land surface hydrological model and machine learning to forecast hourly streamflow over the Yantan catchment, which is one of the cascade reservoirs in the Hongshui River with streamflow influenced by both the upstream reservoir water release and the rainfall runoff process within the catchment.

Before evaluating the streamflow forecast system, it is necessary to investigate the skill by means of a series of specific hindcasts that isolate potential sources of predictability, like meteorological forcing and the initial condition (IC). Here, we use ensemble streamflow prediction (ESP)/reverse ESP (revESP) method to explore the impact of IC on hourly stream prediction. Results show that the effect of IC on runoff prediction is 16 hours. In the next step, we evaluate the hourly streamflow hindcasts during the rainy seasons of 2013-2017 performed by the forecast system. We use European Centre for Medium-Range Weather Forecasts perturbed forecast forcing from the THORPEX Interactive Grand Global Ensemble (TIGGE-ECMWF) as meteorological inputs to perform the hourly streamflow hindcasts. Compared with the ESP, the hydrometeorological ensemble forecast approach reduces probabilistic and deterministic forecast errors by 6% during the first 7 days. After integrated the long short-term memory (LSTM) deep learning method into the system, the deterministic forecast error can be further reduced by 6% in the first 72 hours. We also use historically observed streamflow to drive another LSTM model to perform an LSTM-only streamflow forecast. Results show that its skill sharply dropped after the first 24 hours, which indicates that the meteorology-hydrology modeling approach can improve the streamflow forecast.
Geodynamics of long-term continental subduction and Indian indentation at the India-Eurasia collision zone
Authors: Xue Kai , Schellart Wouter P. , Strak Vincent
Published: March 2022

India-Eurasia convergence velocities have dropped significantly from ~18 cm/yr in the Late Cretaceous-earliest Eocene to ~4-5 cm/yr since ~50 Ma. The mechanisms of convergence deceleration, continued convergence since ~50 Ma, long-term continental subduction and long-term Indian indentation into Eurasia still remain controversial. Many previous studies consider an external driving force for the long-term convergence, continental subduction and Indian indentation, and the initial India-Eurasia collision as the trigger for the deceleration. In this study, we investigate the mechanism(s) of the abrupt deceleration, the continued convergence, the long-term continental subduction and long-term Indian indentation using buoyancy-driven analog experiments. We conduct three large-scale experiments to simulate the subduction and collision process at the convergent boundary with different boundary conditions at the 660-km discontinuity, including an infinite viscosity step (the lower-upper-mantle viscosity ratio (ηLM/ηUM) is infinitely high), no viscosity step (ηM/ηUM =1) and an intermediate viscosity step. The experiment with infinite ηLM/ηUM shows a deceleration when the slab tip reaches the 660-km discontinuity, while the other two experiments show a deceleration at the onset of continental subduction. Our experiments show that a higher ηLM/ηUM favors a lower velocity drop at the onset of continental subduction, lower convergence velocities, reduced continental subduction and a higher indentation amount, and vice versa. Furthermore, our models suggest that in nature, with an intermediate-high ηLM/ηUM, the negative buoyancy force of both upper and lower mantle slab segments is the main driver of long-term convergence, continental subduction and Indian indentation.
Impact of tillage erosion state on 14C labelled assimilate C distribution in a spring rapeseed (Brassica napus L.) soil system and soil C pools
Authors: Pehlivan Ayten , Ruggaber Julian , Remus Rainer , Augustin Jürgen , Kolb Steffen
Published: March 2022

Keywords: 14C pulse labelling, Tillage-erosion, SOC pool, C-undersaturation, C allocation, Climate change.

Tillage erosion is a dominant process on arable land which results in drastic changes in many properties of the topsoil, especially its organic carbon (SOC) content. Particularly on slope positions, some original topsoil is initially displaced toward depressions in the course of a tillage operation. The following tillage then causes nutrient and C-poor subsoil to be mixed into the remaining topsoil. Previous studies have shown that the resulting "C saturation deficit" can lead to increased accumulation of fresh assimilate-C in the soil, i.e., such eroded topsoil can act as a terrestrial carbon dioxide (CO2)-C sink. As a first step, we aim to determine the impact of tillage erosion state (i.e. extent of subsoil admixture) on C dynamics and storage by investigating the distribution of freshly assimilated C in the plant-soil-microbiota system and SOC pools. The soil under investigation was taken from the Ap and Bt horizon of an eroded Luvisol (Nudiargic Luvisol) located on the slopes at the CarboZALF-D site in Dedelow, Germany. This site is a Leibniz Centre for Agricultural Landscape Research (ZALF) experimental site where extensive studies on C dynamics and soil erosion are being carried out. A pot experiment with three simulated tillage erosion states, i.e. moderate, strong and topsoil with no admixture as a reference was carried out by incorporating 12% Bt, 24% Bt and 0% Bt material, respectively. Spring rapeseed (Brassica napus L.) was grown in the pots containing above treatments under controlled conditions as well as pots without plants, with bare soil that were used as control. The plants were pulse labelled with 14CO2 at the stem elongation stage, and the distribution of recently assimilated C into different compartments of plant-soil-soil gas system were assessed after 21 days. Sequential fractionation of the soil samples were carried out and 14C distribution in SOC pools such as dissolved organic carbon (DOC), particulate organic carbon (POM), mineral associated organic matter (MAOM) as well as microbial mass carbon (Cmic) were quantified. We hypothesize that, with increasing subsoil incorporation into the topsoil, the transfer of the freshly assimilated C into the soil and its incorporation into the MAOM pool will intensity.  
In-flight icing: a remote detection tool based on satellite data
Authors: Zollo Alessandra Lucia , Montesarchio Myriam , Bucchignani Edoardo
Published: March 2022

One of the most severe weather hazards to aviation is in-flight airframe icing, i.e. the accretion of ice on airplane’s surfaces during flight. In order to increase margins of aviation safety, the early detection of regions affected by icing conditions is a challenging and desirable goal. In the framework of the H2020 EU project SENS4ICE (SENSors and certifiable hybrid architectures for safer aviation in ICing Environment), CIRA has developed a remote detection tool of icing conditions based on satellite data. Specifically, high-resolution satellite products, based on Meteosat Second Generation (MSG) data, have been considered, with spatial and temporal resolutions of about 3 km and 15 minutes respectively. The aim of this tool is to identify areas potentially affected by in-flight icing hazard, giving information about the severity of the phenomenon (light, moderate or severe) and an estimate of the altitude at which this hazard can occur. The developed algorithm also takes into account supercooled large droplets (SLD), which pose a serious threat to aviation and have been the cause of tragic accidents over the last decades. The tool relies on satellite data, to remotely infer the properties of clouds, and a set of experimental curves and envelopes that describe the interrelationship of cloud liquid water content, mean effective diameter of the cloud droplets and ambient air temperature. These curves, provided by the Federal Aviation Administration (FAA), define the atmospheric icing conditions and represent the reference legislation in this field. Furthermore, a nowcasting algorithm based on the extrapolation in time of the current icing conditions has been implemented, in order to perform a forecast over a short period ahead, responding to the great need for timely and location-specific forecasts that are relevant for aviation, e.g. for safety reasons or for planning and routing air traffic. This presentation will provide a preliminary analysis of the performance of the implemented tools, which will be evaluated in relevant icing conditions in the framework of SENS4ICE flight campaigns, planned for 2023.

Acknowledgment: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N° 824253 (SENS4ICE project).
Determination of the appropriate baseflow separation method for gauging stations on the two lowland rivers in Croatia
Authors: Lacko Martina , Potočki Kristina , Gilja Gordon
Published: March 2022

The estimation of baseflow is one of the essential tasks in water resources management and hydrologic research to assess the impacts of climate change and to describe and predict flood events based on the flood hydrograph characteristics (peak flow, duration and volume). Several methods have been developed to separate baseflow from direct flow, and in recent years they have been automated through the use of available R packages. In this work R programming language packages “EcoHydRology” and “lfstat” were used to separate baseflow from direct flow on the historical daily discharge time series of the several gauging stations on the two large lowland rivers in Croatia: the Sava River and the Drava River. The aim of this study is to determine the appropriate baseflow separation method for gauging stations on Sava River and Drava River in order to evaluate the baseflow separation method for future multivariate analysis of flood events under the R3PEAT project (www.grad.hr/r3peat) that explores pier scour development next to the bridges crossing large rivers in Croatia with installed scour countermeasures.
Coupling regional air quality simulations of EURAD-IM with street canyon observations - a machine learning approach
Authors: Neubacher Charlotte , Franke Philipp , Heinlein Alexander , Klawonn Axel , Kiendler-Scharr Astrid , Lange Anne-Caroline
Published: March 2022

State of the art atmospheric chemistry transport models on regional scales as the EURAD-IM (EURopean Air pollution Dispersion-Inverse Model) simulate physical and chemical processes in the atmosphere to predict the dispersion of air pollutants. With EURAD-IM’s 4D-var data assimilation application, detailed analyses of the air quality can be conducted. These analyses allow for improvements of atmospheric chemistry forecast as well as emission source strength assessments. Simulations of EURAD-IM can be nested to a spatial resolution of 1 km, which does not correspond to the urban scale. Thus, inner city street canyon observations cannot be exploited since here, anthropogenic pollution vary vastly over scales of 100 m or less.

We address this issue by implementing a machine learning (ML) module into EURAD-IM, forming a hybrid model that enable bridging the representativeness gap between model resolution and inner-city observations. Thus, the data assimilation of EURAD-IM is strengthened by additional observations in urban regions. Our approach of the ML module is based on a neural network (NN) with relevant environmental information of street architecture, traffic density, meteorology, and atmospheric pollutant concentrations from EURAD-IM as well as the street canyon observation of pollutants as input features. The NN then maps the observed concentration from street canyon scale to larger spatial scales.

We are currently working with a fully controllable test environment created from EURAD-IM forecasts of the years 2020 and 2021 at different spatial resolutions. Here, the ML model maps the high-resolution hourly NO2 concentration to the concentration of the low resolution model grid. It turns out that it is very difficult for NNs to learn the hourly concentrations with equal accuracy using diurnal cycles of pollutant concentrations. Thus, we develop a model that uses an independent NN for each hour to support time-of-day learning. This allows to reduce the training error by a factor of 102. As a proof of concept, we trained the ML model in an overfitting regime where the mean squared training error reduce to 0.001% for each hour. Furthermore, by optimizing the hyperparameters and introducing regularization terms to reduce the overfitting, we achieved a validation error of 9−12% during night and 9−16% during day.
Hillslope failure due to stream undercutting: The 2021 flood event in the Ahr-valley and resulting mass movements – a multi-method approach
Authors: Wenzel Till , Bell Rainer , Dietze Michael , Schrott Lothar , Beer Alexander , Braun Anika , Fernandez-Steeger Tomas
Published: March 2022

Exceptional rainfalls (up to 200 mm in 72 h) in W-Germany, the Netherlands and Belgium led to severe flooding on 14-15 July 2021. In Germany the Ahr valley (Eifel mountains) was hit heavily, leading to 134 fatalities and substantial loss of property and infrastructure. Besides the damage in the floodplains, multiple shallow landslides were triggered along the Ahr embankments. Furthermore, the flood caused undercutting of several old landslide bodies. One such landslide in Devonian Schist bedrock is located at a narrow, bended stretch of the Ahr, near the town of Müsch. A complete failure has the potential to dam the river posing a considerable hazard.

The main objectives of this study are to gain an in-depth understanding of the landslide causes and its transient activity. These objectives are tackled by a multi-method approach: landslide mapping, analysis of pre- and post-event airborne laser scanning (ALS) and terrestrial laser scanning (TLS) data, electrical resistivity tomography (ERT), seismic refraction tomography (SRT), passive seismic monitoring, geotechnical analysis and interviews with local inhabitants.

The old landslide is 100 m wide and 200 m long. Preliminary analysis of ERT and SRT indicate a landslide depth of 20-30 m, leading to an overall landslide volume of 400,000 - 600,000 m³. ERT further shows underlying bedrock properties and water saturated zones. An old dumpsite as well as an ancient railway, now used as forest trail, cutting through the landslide horizontally are clearly shown as resistive zones. Analysis of ALS data shows that so far only the frontal part at the Ahr banks has been active and has lost about 6300 m³ due to fluvial erosion and landsliding. Field mapping shows clear signs of retrogressive landsliding. From October 2021 onwards the landslide body has been equipped with five geophones to record both subtle changes in ground rheology and discrete events of rock bridge failure due to incremental mass movement. Currently most seismic signals at the slope can be allocated to daily traffic and road construction in the area.

The combination of geophysical and remote sensing methods enables a profound insight into the mechanisms and present processes of the Müsch landslide. Based on this, we will be able to assess the probability for a reactivation of the whole landslide body, which could trigger cascading hazards affecting a much larger region. An improved monitoring concept will be developed which can be adopted to similar structures in the Ahr valley and beyond. 
The effect of differing drought-heat signatures on terrestrial carbon dynamics and vegetation composition: a multi-model comparison
Authors: Tschumi Elisabeth , Lienert Sebastian , Bastos Ana , Gregor Konstantin , Joos Fortunat , Knauer Jürgen , Pongratz Julia , Rammig Anja , Thiery Wim , van der Wiel Karin , Wey Hao-wei , Williams Karina , Yao Yi , Zaehle Sönke , Zscheischler Jakob
Published: March 2022

The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, their impacts on the terrestrial biosphere and the anthropogenic CO2 sink remain poorly understood. Here we analyse the effects of six hypothetical climate scenarios with stationary climate but differing drought-heat signatures on vegetation distribution and land carbon dynamics, as modelled by seven state-of-the-art dynamic global vegetation models. The six forcing scenarios are sampled from a long climate model simulation and consist of a control scenario representing a natural climate, a scenario with no hot and dry extremes, one with no compound hot and dry extremes but univariate extremes are possible, one with only hot extremes, one with only dry extremes, and one with both hot and dry extremes. Models show substantial differences in their vegetation coverage response to the different scenarios. While in some models, climate with no droughts and heatwaves favours tree growth, this is not the case for other models, where grasses benefit. Similarly, climates with frequent droughts promote grasses in some models and reduce forest growth in others. Models tend to agree that a climate with frequent concurrent droughts and heatwaves leads to reduced tree cover and increased grass cover. The changes in coverage are mirrored by changes in gross and net carbon fluxes. The stark differences among model responses illustrate the different modelling processes dealing with heat and drought stress and how they are differently affected by the extremes. Overall, this comparison helps quantify model uncertainties and process differences that are important for how vegetation behaves under extreme climate events.

Our study illustrates how factorial model experiments can be employed to disentangle the impacts from single and compound extremes. The findings from this model comparison may also help to identify sources of uncertainty in carbon cycle projections.