bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling the dispersion of particle number concentrations in the West Midlands, UK
Authors: Zhong Jian , Harrison Roy
Published: February 2023

Ultrafine particles (UFPs with a diameter less than 100 nm) are tiny and respirable particles. Because of their small sizes, UFPs can penetrate cells and tissue, accumulate in lungs, and cause health effects. Although UFPs are currently not regulated in the same way as mass concentrations for large particles such as PM2.5 and PM10, the 2021 WHO global air quality guidelines have highlighted the pressing issue of UFPs with a good practice statement. Particle number concentrations (PNC) are the most common measure for UFPs with tiny mass. UFPs often dominate the total ambient PNC in urban environments. There is a strong need to quantify the PNC in the ambient air through measurements and modelling. This study simulates the dispersion of particle number concentrations in the West Midlands (WM), UK using the local scale ADMS-Urban model, which is an advanced quasi-Gaussian plume dispersion modelling system. ADMS-Urban implements a physics-based approach to represent the characteristics of the atmospheric boundary layer. It can represent a variety of source types (such as road and grid emissions) occurring in urban environments and requires a range of input data. Grid sources of PNC for SNAP (Selected Nomenclature for Air Pollution) sectors across the WM were obtained from TNO. Road sources were derived based on the local traffic activity maps (from Transport for West Midlands and Birmingham City Council) and PNC emission factors available in the literature. Meteorological data for Birmingham Airport was used to drive the dispersion. Particle number was used as a passive scalar, with no inclusion of aerosol microphysics. Background data from the rural Chilbolton air quality site was downloaded from Defra UK-Air website. Advanced canyon and urban canopy parameters were derived based on the building data and road network shapefiles using ArcGIS tools. The model was run on the University of Birmingham’s BlueBEAR HPC. Model evaluation was conducted by comparing the modelled (from a receptor run) and measured data at the Birmingham Air Quality Supersite. Overall, the model performed well. Based on the modelling output from a contour run, street scale resolution maps for annual PNC were generated, which could be linked to local population and health data for potential epidemiological studies.        
Coastal Groundwater Discharge Simulations/Models for Mobile Bay
Authors: Richins John , Befus Kevin , Rodgers Kirk
Published: February 2023

Terrestrial groundwater discharges to coastal drainage networks as baseflow and to coastal waters as fresh submarine groundwater discharge. If groundwater discharge comprises a large portion of inflow or has a different composition than the receiving waters, these groundwater fluxes can strongly influence the water quality of coastal waters. However, the spatial distribution of such fluxes makes quantifying the net effect of groundwater discharge difficult with field data. Furthermore, future climate conditions may change how groundwater interacts with surface water through changes in precipitation, evapotranspiration, and sea level. Mobile Bay is at the nexus of anthropogenic-driven sea level rise and water quality issues, making it an ideal study location. Therefore, we are developing and calibrating MODFLOW-based groundwater flow models using scripted workflows within the Python programming language and the FloPy library to investigate three questions: 1) How much groundwater discharge occurs, 2) where does the groundwater discharge occur, and 3) how do environmental variations associated with climate change affect the location and volume of groundwater discharge to Mobile Bay. By answering these three questions, we will provide valuable knowledge regarding variations in the magnitude and location of coastal groundwater discharge due to possible environmental changes.
The influence of slab window asthenospheric flow on intraplate volcanism, dynamic uplift, and present-day mantle heterogeneity in East Asia
Authors: Brown Hamish , Ma Jincheng , Colli Lorenzo , Bunge Hans-Peter
Published: February 2023

It is generally accepted that East Asian mantle dynamics has been dominated by subduction and downwelling since Mesozoic times (e.g. Müller et al. (2016)). However, seemingly in contrast to this history, a variety of observations indicate a presence of anomalously hot asthenospheric material beneath East Asia during the late Cenozoic. First of all, tomographic models consistently reveal an extensive network of seismically slow anomalies at asthenospheric depths, which align spatially with a recent (< 30 Ma) phase of intraplate volcanism. The influence of this positively buoyant material at the surface is further highlighted by induced dynamic uplift, which is recorded in the geological record through an inter-regional sedimentary hiatus during the late Eocene—Oligocene. Residual topography studies additionally find swells of dynamic uplift throughout this region in the present day. Global mantle circulation models (MCMs) show that these observations can be reproduced in a subduction-dominated region by the spillover of anomalously hot asthenospheric material from the adjacent Pacific domain during ridge subduction events. In particular, the subduction of the Izanagi-Pacific ridge at ~55 Ma provides a large window through which Pacific asthenosphere could have flowed into East Asia. We test this hypothesis by comparing these MCMs to a variety of geological observations, including the distribution of sedimentary hiatus and intraplate volcanism during the late Cenozoic. We additionally compare the present-day distribution of hot material predicted by these models with the recently published full waveform inversion tomographic model of the region, Sinoscope 1.0, which highlights the distribution of seismically slow anomalies beneath the region. We find an encouraging match between asthenospheric flow predicted by these models and the observations considered, showing this to be a viable new hypothesis in explaining these observations. The mechanism of hot asthenospheric build-up during subduction and release during slab window opening may not be limited to East Asia, and could reconcile observations of intraplate volcanism and dynamic uplift in convergent regions more generally. 
Implementation of form drag scheme into NEMO sea ice model SI3
Authors: Schroeder David , Feltham Danny
Published: February 2023

The efficiency of air-sea momentum depends on top and bottom sea ice surface roughness which varies with ice types and conditions, but constants are applied in most climate models. Future sea ice reduction will entail an increase in efficiency of air-sea momentum transfer. A high physical process fidelity will be a requirement for realistic model predictions. Within the CANARI project (Climate change in the Arctic-North Atlantic Region and Impacts on the UK) the form drag scheme from the sea ice model CICE is implemented into the NEMO sea ice model SI3. Based on parameters of the ice cover such as ice concentration, size, and frequency of the sails and keels, freeboard and floe draft, and size of floes and melt pond fraction, the total form drag can be computed as a sum of form drag from sails and keels, form drag from floe edges, form drag from melt pond edges, and a reduced skin drag due to a sheltering effect. Historical simulations are presented discussing the impact on sea ice dynamics and mass balance separating the contributions from modified momentum and heat transfer.
Controls on the flow configuration of Vanderford Glacier, East Antarctica
Authors: McCormack Felicity , Kulessa Bernd , Roberts Jason
Published: February 2023

Vanderford Glacier is one of the fastest retreating glaciers in East Antarctica, with approximately 18.6 km of grounding line retreat since 1996. Together with the Totten Glacier, the Vanderford Glacier is a key outlet glacier of the Aurora Subglacial Basin (ASB), which contains approximately 7 m of global sea level equivalent, of which ~3.5 m is vulnerable to ocean driven melting, and is rapidly losing mass. While the Totten Glacier currently discharges almost twice as much ice as the Vanderford Glacier, sediment records from the Sabrina and Knox Coast Sectors indicate that the Vanderford Glacier has had sedimentation rates over twice that at Totten in the past. Here, we examine the current flow configuration between Vanderford and Totten Glaciers and drivers of it, including interactions between the subglacial topography, hydraulic potential, climate, and ice sheet dynamics. We use the Ice-sheet and Sea-level System Model (ISSM) under experiments of heightened ocean warming concentrated at Vanderford Glacier, and heightened surface mass balance at Totten Glacier, to show that the present-day flow configuration between the Totten and Vanderford Glaciers is tenuous. Rerouting towards Vanderford Glacier could occur under even minor changes in surface elevation at both glaciers. Such rerouting potentially exposes large parts of the underbelly of the ASB to enhanced ocean-driven ice shelf melting in the event of rapid retreat of Vanderford Glacier, with implications for global sea level rise.
The velocity of climate change revisited: Smooth velocity field and ecological relevance
Authors: Kasparian Jérôme , Gaponenko Iaroslav , Moinat Laure , Rohat Guillaume , Goyette Stéphane , Paruch Patrycja
Published: February 2023

Describing climate change in terms of spatial velocity is essential to assess the ability for ecosystems or individual species to migrate at a sufficient pace to keep environmental conditions allowing their survival. While climate models provide a temporal evolution of a number of  variables at each point of their computational grid, Loarie et al. introduced a velocity of climate change, defined as the ratio of the temporal derivative to the spatial gradient of temperature, or any other variable such as precipitations [1]. This amounts to assume that isotherms shift along the temperature gradient. Although intuitive, this idea is mathematically correct only for straight isotherms parallel to each other [2]. Whenever this condition is not met, e.g., due to complex topography or coastlines, the gradient-based velocity field will display artefacts in the form of local convergence or divergence that are likely to bias the analysis.We show that these artefacts can be fixed by defining a much more regular velocity field. This alternative approach to the velocity of climate change determines the direction of the velocity vector by minimising the local vorticity rather than by the gradient. From a fundamental point of view, the resulting smoother velocity field allow an analysis at finer temporal and spatial scales. It also allows to define the climate trajectory of a given origin point. Our approach also provides tools to estimate the stability of climate trajectories depending on the behaviour of their "return" trajectory obtained by reversing time [3].  From an ecological point of view, we discuss preliminary results on the relevance of each definition of the velocity of climate change, based on comparisons of the obtained climate trajectories with ecological trajectories from observational data relative to species distribution areas.References

1. S. R. Loarie et al., Nature 462, 1052 (2009)
2. J. Rey, G. Rohat, M. Perroud, S. Goyette, J. Kasparian, Env. Res. Lett. 15, 034027 (2020)
3. I. Gaponenko, G. Rohat, S. Goyette, P. Paruch, J. Kasparian, Sci. Rep., 12, 2997, (2022)
Investigation of Secondary Gravity Wave Variability using a 3-Field-of-View Doppler-Rayleigh Lidar in Kühlungsborn, Germany
Authors: Wing Robin , Gerding Michael , Baumgarten Gerd , Strelnikova Irina , Franco-Diaz Eframir , Mossad Mohamed
Published: February 2023

Recent interpretations of atmospheric gravity wave propagation have emphasized the importance of secondary and higher-order gravity waves.  One implication of multi-stage vertical coupling of gravity waves could be an increased probability of measuring larger vertical wavelengths than would be expected from a primary gravity wave.  These secondary waves are also expected to be intermittent in time and localized in space, which means that lidars are an excellent technique for detecting these phenomena.  We present lidar gravity wave measurements from temperatures and winds using a zenith pointing beam and two 25-degree off-zenith beams. In each lidar field-of-view, gravity wave energy is estimated as a function of vertical wavelength and period using a Morlet wavelet analysis.  This analysis is conducted at multiple altitudes in each of the three beams to determine small-scale horizontal variability, which could indicate small-scale wave activity associated with primary wave breaking.
Global and regional anthropogenic emissions inventories for air quality atlases
Authors: Soulie Antonin , doumbia Thierno , Keita Sekou , Granier Claire , Denier Vand der Gon Hugo , Kuenen Jeroen , Arellano Santiago , Darras Sabine , Gauss Michael , Guevara Marc , Jalkanen Jukka-Pekka , Liousse Cathy , Simpson David , Sindelarova Katerina
Published: February 2023

We present two inventories of anthropogenic emissions as well as an air quality atlas linked to Copernicus, the European earth observation system. CAMS-GLOB-ANTv5.3, a global anthropogenic emissions inventory, has been developed and provides emission data for the major atmospheric pollutants and greenhouse gases, as well as 25 speciated Volatile Organic Compounds (VOCs), for the period 2000-2023. This inventory is used as input for the Copernicus Atmosphere Monitoring System (CAMS) atmospheric reanalysis and forecasts.A mosaic inventory of anthropogenic emissions was also developed as part of the Copernicus CO2 project (CoCO2) focusing on greenhouse gases emissions. This mosaic uses the CAMS-GLOB-ANTv5.3 inventory as a global basis, and the DACCIWA2 (Dynamics-Aerosol-Chemistry-Cloud interactions in West Africa) inventory, a regional African emissions inventory. DACCIWA2 provides 0.1x0.1 degree resolution emissions of greenhouse gases and atmospheric pollutants for the period 2010-2018.The CAMS reanalysis is being used to develop an atlas of air quality called AQWA (Air Quality Worldwide Atlas). The AQWA atlas gives precious information about historical, climatological and current atmospheric composition, as well as air quality indexes. These statistics are available for all countries around the world, as well as states/provinces for the United States and China.This presentation describes the methodology used to develop and evaluate the two inventories and shows a few visualization examples from the atlas, which is still in development.
Feeding the flames: how colonialism led to unprecedented wildfires across SE Australia
Authors: Mariani Michela , Connor Simon , Fletcher Michael-Shawn , Haberle Simon , Stevenson Janelle , Kershaw Peter , Herbert Annika , Theuerkauf Martin , Bowman David
Published: February 2023

The Black Summer bushfires (2019-2020) cost the Australian economy over 100 billion dollars and burnt a total of 18 million hectares. In just one season, around 20% of Australia's Eucalyptus forests burnt down and billions of animals perished. Recent catastrophic fires in Australia and North America have made scientists and policymakers question how the disruption of First Nations' burning practices has impacted fuel loads. For instance, we have learnt from modern Australian Indigenous communities, historical literature, and art works that Indigenous peoples have used cultural burning to rejuvenate patches of land and preserve open vegetation for hunting and cultural purposes. The advent of British invasion brought a change in the type of fire regimes and landscape management across much of the continent, which may have led to an increase in flammable fuels in forest settings. However, the actual degree of land-cover modification by early settlers has only been often debated in the academic literature and within management stakeholders.The quantification of past land cover is needed to address such debates. Pollen is the key proxy to track past vegetation changes, but pollen spectra suffer from some important biases e.g. taphonomy, pollen productivity, dispersal capability. Estimating past vegetation cover from sedimentary pollen composition requires to correct for productivity and dispersal biases using empirical-based models of the pollen-vegetation relationship. Such models for quantitative vegetation reconstruction (e.g. REVEALS) have yet been mostly applied in the Northern Hemisphere in the last 15 years - here we present recent applications of this methodology from Australia. We show the quantification of land cover changes through pre- and post- British invasion on multiple records (n=51) across the southeastern Australian region. This represents the first regional application of REVEALS within the Australian continent.We provide the first empirical evidence that the regional landscape before British invasion was a cultural landscape with limited tree cover as it was maintained by Indigenous Australians through cultural burning. Our findings suggest that the removal of Indigenous vegetation management has altered woodland fuel structure and that much of the region was predominantly open before colonial invasion. The post-colonial land modification has resonance in wildfire occurrence and management under the pressing challenges posed by climate change.
Another bend in the orogen? Kinematics of the winding Mexican Fold-and-Trust Belt: Paleomagnetism of the Nazas arc.
Authors: Guerra Roel Rafael , Pastor Galán Daniel , Chávez Cabello Gabriel , Ramírez-Peña César Francisco , Aranda Gómez José Jorge , Patiño Méndez Gerardo , Rodríguez-Parra Alejandro , Nova Rodríguez Eduer Giovanny , Molina Garza Roberto Stanley
Published: February 2023

The Mexican Fold-and-Trust Belt is a winding belt that formed after a series of protracted tectonic events, which began with the onset of sedimentation in the basins formed during the break-up of Pangea and during the roll-back of the oceanic Kula plate in Jurassic times. Later, the continued subduction of Kula-Farallon constituent plates at the western margin of Mexico triggered arc formation, thrusting, basin inversion, and folding. The kinematics of the fold-and-thrust belt curvature at regional and local scales is still debated. Different hypotheses have been explored to explain the trace of the orogen: 1) curvature is mainly and primarily controlled by the basin architecture; 2) Curvature is progressive and was at least partially acquired during deformation being controlled by the basement geometry, lithologic heterogeneities, and/or the shortening direction, and 3) The curvature is, at least partially, postdating the main orogenic deformation structures being formed as the youngest of the deformation phases. Several regional-scale studies have been performed (Eguiluz et al., 2010; Fitz-Diaz et al., 2017). But most of the previous paleomagnetic studies were focused on studying the configuration of the desegregated fragments of Pangea (Molina-Garza et al., 1992). In this study, we investigate the nature of the curvature in the north and central-eastern part of the Mexican Fold and Trust Belt using paleomagnetic data obtained from the Jurassic rocks of the Nazas Formation, this formation is composed of a volcanic and volcano-sedimentary succession of andesites and dacite flows interbedded with tuff deposited in an intra-arc or back-arc setting. Our results show remagnetizations, some potential primary magnetizations, and significant counterclockwise rotations. This implies a potential oroclinal bending origin for at least part of the Mexican fold-and-thrust-belt curvature. This contribution will discuss the potential mechanisms causing the curvature and the implications for the kinematics, tectonic and geodynamic evolution of the central-western Pacific subduction during the Mesozoic-Paleogene in northeastern Mexico. This work is a posthumous contribution of Dr. Roberto Stanley Molina-Garza and a tribute to his huge contribution to the understanding of the tectonic history of Mexico.Keywords: Paleomagnetism; Mexican Fold and Trust Belt; Anticlockwise rotation; Remagnetization; Jurassic; Nazas Arc.
Anomalous mass gain of a tidewater outlet glacier with rapidly thinning ice sheet margin in Greenland
Authors: Dachauer Armin , Vieli Andreas
Published: February 2023

In response to the general warming ocean-termination outlet glaciers of the Greenland ice sheet are generally thinning and retreating rapidly. However, the glacier system of Qajuuttap Sermia (also known as Eqalorutsit Kangilliit Sermiat), at the southwestern basin of the greenland ice sheet, shows a strongly contrasting and highly heterogenous dynamical behaviour. Detailed analysis of elevation changes (AeroDEM, GIMP, ArcticDEM) and front positions between the years 1985 and 2021 show slight but significant advance and thickening over at least the last 35 years, whereas its neighboring ocean- and land-terminating glaciers and more interestingly its three direct northwestern tributaries all show rapid thinning. The data indicates that effects of fjord geometry alone cannot explain this anomaly and we therefore further investigate potential reasons using operational continuous time series of solid ice flux (PROMICE) and surface mass balance from regional climate models (RACMO, MAR). 
Sequential simulation-optimization of a borehole heat exchanger field considering variability in heating demand and subsurface thermal responses
Authors: Soltan Mohammadi Hesam , Ringel Lisa Maria , Bayer Peter
Published: February 2023

In installations with multiple borehole heat exchangers (BHEs), neighboring BHEs commonly influence each other. Imbalanced heat extraction and operation over many years thus causes growing interference and a pronounced thermal anomaly in the ground. This may not only have detrimental environmental effects but hamper the long-term efficiency of the entire system. As a remedy, concepts for adjusting the geometric layout and individual heat extraction loads of BHEs to a given site condition and heat demand have been presented. However, the more critical question is how to obtain an optimal and well-controlled system during the entire lifespan that often covers decades. In most of the optimization concepts that have been developed so far, the optimal load distribution is calculated on the basis of an estimated fixed heating demand. It is clear that this is not a realistic assumption due to various reasons such as changing weather conditions or a shift in consumption behavior. In our presentation, a more flexible combined simulation-optimization is introduced that takes into account a fluctuating heat demand at a monthly resolution. Here, in case of a deviation from the predefined heating demand, the BHE loads are revised and adjusted to the new conditions. Another aspect that can be considered in this sequential updating procedure is the inaccuracy of the model predicting the heat transport mechanisms in the subsurface. The new sequential optimization allows accepting a margin of uncertainty in subsurface thermal responses and taking into account thermal conditions in the ground that differ from what has been initially predicted. In our work, for demonstration, a heat demand profile with a series of monthly variations as well as a range of uncertainties in the measured temperatures of some individual boreholes in a BHE field is chosen. The optimization problem is solved efficiently by linear programming. To demonstrate the capability of the sequential procedure, fields with different densities and configurations of BHEs are studied.
Comparison of Fence Line Monitoring by mobile monitoring vehicle and Chimney Measuring Devices in Large Industrial Complexes
Authors: Sim Juhyeon , Kim Dukhyeon , Shin Juseon , Lee Yuseon , Joo Sohee , Kim Jaewon , Park Gahyeon , Noh Youngmin
Published: February 2023

In the case of large industrial complexes, there are state management equipment to monitor pollutants emitted from chimneys, but there are undetected sources of pollution, such as leaks during processes, leaks from pipes, and leaks from unsealed warehouses, except for chimneys. In this study, mobile observation was conducted using SOF, Sky DOAS, in-situ MeDOAS, and MeFTIR equipment. The observation method used in this study is fence line monitoring, which surrounds a large factory area and observes both the upwind and downwind sides. method of observation. The observation site was conducted in July and August 2021 at the Yeosu Industrial Complex located in Yeosu, Jeollanam-do, South Korea, one of the three largest industrial complexes in South Korea. In order to find out whether and the extent of leakage, four areas where Telemonitoring System(TMS), a chimney measuring device managed by the Korea Environment Corporation, exist were designated as observation sites. The results observed for the same period of time were compared for SO2 and NO2, which are substances with overlapping measurement items of mobile monitoring vehicle(MMV) and TMS. Although a direct comparison was not possible because the MMV expresses the emission per hour and the TMS expresses the emission concentration, it was confirmed that leaks that were not captured by the TMS on a specific date appeared as a result of the MMV measurement. This study confirmed that even in industrial complexes where TMS is installed for management purposes, air pollution and economic losses due to leaks can be reduced if fan line monitoring is conducted to detect unexpected leaks. acknowledgmentThis work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2018R1D1A3B07048047) 
The Three-Dimensional Visualization of Mars Dust Storms Based on Deriving Digital Elevation Maps from Satellite Imagery
Authors: Alzeyoudi Meirah , Gebhardt Claus
Published: February 2023

The focus of this presentation is the three-dimensional visualization of Mars dust storms from spacecraft images. The dust storm height is determined by their shadows. Image parameters such as the solar incidence angle, solar azimuth angle, latitude, and longitude are taken into account. Interactive three-dimensional maps of dust storms are created. This presentation includes satellite images from MARCI/MRO (Mars Color Imager/Mars Reconnaissance Orbiter) in the years 2020-2021. This adds to a better understanding of Mars dust storms. This works uses the MeteoMARS tool [1], the NASA PDS Imaging Node [2], the NASA Integrated Software for Imagers and Spectrometers, and the QGIS software [3].[1] http://meteomars.pamplonetario.org/[2] https://pds-imaging.jpl.nasa.gov/[3] https://www.qgis.org/en/site/
Reductions in land surface temperature induced by forest management in Fennoscandia revealed by machine learning models
Authors: Huang Bo , Li Yan , Liu Yi , Hu Xiangping , Zhao Wenwu , Cherubini Francesco
Published: February 2023

Forests affect the local climate through a variety of biophysical mechanisms. Observational and modelling studies have investigated the effects of forested vs. non-forested areas, but the influence of forest management on surface temperature has received far less attention owing to the inherent challenges to adapt climate models to cope with forest dynamics. Further, climate models are complex and highly parameterized, and the time and resource intensity of their use limit applications. The availability of simple yet reliable statistical models based on high resolution maps of forest attributes at various development stages can link individual forest management practices to local temperature changes, and ultimately support the design of improved strategies. In this study, we investigate how forest management influences local surface temperature (LST) in Fennoscandia through a set of machine learning algorithms. We find that more developed forests are typically associated with higher LST than young or undeveloped forests. The mean multi-model estimates from our statistical system can accurately reproduce the observed LST. Relative to the present state of Fennoscandian forests, an ideal scenario with fully developed forests is found to induce an annual mean warming of 0.26 ℃ (0.03/0.69 ℃ as 5th/95th percentile), and an average cooling effect in the summer daytime from -0.85 to -0.23 ℃ (depending on the model). On the contrary, a scenario with undeveloped forests induces an annual average cooling of -0.29 ℃ (-0.61/-0.01 ℃), but daytime warming in the summer that can be higher than 1 ℃. A weak annual mean cooling of -0.01 ℃ is attributed to historical forest harvest that occurred between 2015 and 2018, with an increased daytime temperature in summer of about 0.04 ℃. Overall, this approach is a flexible option to study effects of forest management on LST that can be applied at various scales and for alternative management scenarios, thereby helping to improve local management strategies with consideration of effects on local climate. A machine learning based statistical system is used to predict effects of forest management on LST
The system can accurately reproduce the observed LST in Fennoscandian forests
More developed forests are typically associated with higher LST than young or undeveloped forest
Historical forest management had a light mean annual cooling, but increased LST in the summer
The approach is flexible and can be applied at various scales and different management scenarios
 KeywordsForest management, climate change, surface temperature, machine learning, statistical model
Are outstanding spectral solitons indicators for rogue waves in JONSWAP seas?
Authors: Lee Yu-Chen , Wahls Sander
Published: February 2023

Rogue waves are large individual waves whose height is more than twice of the significant wave height. They have the potential to severely damage offshore structures. For this reason, there is a large interest in characteristing rogue waves. A recent study of rogue waves at a shallow water site in the southern North Sea by Teutsch et al. (2022) has revealed that, at this site, the presence of a large outstanding soliton in the nonlinear Fourier spectrum indicates a high probability of rogue wave occurrence.We are interested to see if this indicator is site specific. Here, we will analyse time series obtained from JONSWAP spectra by the nonlinear Fourier transform (NFT). The NFT enables to decompose a signal into components based on their governing nonlinear evolution equations, i.e. the Korteveg-de Vries (KdV) equation for shallow water waves and the nonlinear Schrödinger (NLS) equation for deep water waves. We will investigate if the outstanding soliton indicator also applies to simulated data in shallow and deep water. We will furthermore propagate time series using the KdV and NLS equations, respectively, in order to check how many non-rogue waves with large outstanding soliton in nonlinear spectrum become rogue waves after propagation.
The Making of Ynyslas: communicating change through the visual impact of a drowned landscape
Authors: Mason John
Published: February 2023

 Ynyslas National Nature Reserve is a shingle-spit and sand dune complex on the western coast of Wales. In its hinterland are extensive estuarine flats, shifting sandbanks and deep channels. The shingle-spit fronts a wide sandy beach that uncovers at low tide, featuring extensive peat deposits of mid-Holocene and younger ages (6-4.7 KYA). Set in the peat are the stumps of the famous Submerged Forest, consisting of alder, birch, oak and pine that once flourished here before rising water-levels drowned them. Offshore in Cardigan Bay, although extensively reworked Quaternary glaciogenic sediments predominate, similar but either older or undated peatlands have been encountered sporadically in boreholes, one undated example being twenty meters beneath the sea bed in a water depth of 20 m. Clearly these and the Submerged Forest record parts of the post-glacial marine transgression that created the shallow (typically <<50 meters) Cardigan Bay over several thousand years following the onset of the Holocene. The fact that the results of the transgression can be so starkly seen at low tide, coupled with the offshore borehole records, provides a stark reminder of the effects of climate change, of which sea level rise is probably the greatest threat to communities along the Welsh coast. Such straightforward evidence for the effects of climate change provides an excellent opportunity to further explore topics around both its causes and its effects, using a narrative of what actually happened, based on the scientific literature. The Making of Ynyslas (2019) is that narrative and has proved to be an effective method of outreach based around this highly popular (250 K visitors per year) destination. Given that the post-glacial transgression was global in nature, other such science-communication opportunities are likely to present themselves elsewhere.
Planar Electrostatic Gravity Gradiometer GREMLIT
Authors: Portier Nolwenn , Liorzou Françoise , Lebat Vincent , Christophe Bruno , Dalin Marine , Gierse Andreas
Published: February 2023

Based on the strong experience acquired through the development of ultra-sensitive electrostatic accelerometers for the GRACE, GOCE and GRACE FOLLOW-ON satellite gravity missions, ONERA is developing a new concept of gravity gradiometer (GREMLIT) for airborne survey. Using a control loop, four proof masses are maintained motionless with respect to the surrounding electrodes. The applied electrostatic forces needed for this control, are linked to the accelerations suffered by each proof mass. Observation of differences in the four proof-mass acceleration outputs inform on the horizontal gravity gradient with an expect accuracy of one Eötvös (10-9 s-2) in laboratory. The adaptation of GREMLIT to airborne conditions requires the cancellation of the acceleration gradiometer common-mode, which is done by integrating GREMLIT on a controlled platform. The operability of GREMLIT in aircraft therefore depends on the stabilizer platform ability to retrieve the parasitic aircraft accelerations, which constitutes a real technical challenge. The presentation will emphasize the conception and development of this stabilizer system and the next steps of the project with hopefully, a first mobile acquisition performed by the end of 2023.
Decomposition learning based on spatial heterogeneity: A case study of COVID-19 infection forecasting in Germany
Authors: Cheng Ximeng , Arndt Jost , Marquez Emilia , Ma Jackie
Published: February 2023

New models are emerging from Artificial Intelligence (AI) and its sub-fields, in particular, Machine Learning and Deep Learning that are being applied in different application areas including geography (e.g., land cover identification and traffic volume forecasting based on spatial data). Different from well-known datasets often used to develop AI models (e.g., ImageNet for image classification), spatial data has an intrinsic feature, i.e., spatial heterogeneity, which leads to varying relationships across different regions between the independent (i.e., the model input X) and dependent variables (i.e., the model output Y). This makes it difficult to conduct large-scale studies with a single robust AI model. In this study, we draw on the idea of modular learning, i.e., to decompose large-scale tasks into sub-tasks for specific sub-regions and use multiple AI models to achieve these sub-tasks. The decomposition is based on the spatial characteristics to ensure that the relationship between independent and dependent variables is similar in each sub-region. We explore this approach for forecasting COVID-19 cases in Germany using spatiotemporal data (e.g., weather data and human mobility data) as an example and compare the prediction tasks with a single model to the proposed decomposition learning procedure in terms of accuracy and efficiency. This study is part of the project DAKI-FWS which is funded by the Federal Ministry of Economic Affairs and Climate Action in Germany to develop an early warning system to stabilize the German economy.
HCDC datasearch portal: Replacing legacy solutions with a unified open-source portal
Authors: Baldewein Linda , Dibeh Housam , Sommer Philipp S. , Kleeberg Ulrike
Published: February 2023

In Earth System Sciences, new data portals are currently being developed by what seems to be each new project and research initiative. But what happens to already existing solutions that are in a dire need of a software update? We will introduce the HCDC datasearch portal (https://hcdc.hereon.de/datasearch/), an open-source software solution, that combines data from a legacy database, file storage systems, OGC conform web services and a World Data Center. Our portal provides a common interface for all our heterogeneous data-sources to select and to download the data-products based on filters for metadata and spatio-temporal information.Three legacy portal solutions at Helmholtz-Zentrum Hereon are replaced by a scalable and easily extendable new portal based on an Elasticsearch cluster in the back-end and a user-friendly web interface as well as a machine readable API in the front-end. To ensure software that fits the user’s workflows, a stakeholder group was involved from the early stages of the planning up until the release of the final product.Extensibility of the portal is ensured by only storing metadata within the portal. Data access and download is configured based on each decentralized storage solution, e.g. a local database or a World Data Center. Harmonization of metadata is crucial for the user experience of the portal. We limited the searchable metadata to 14 fields in addition to geospatial and temporal metadata, including information such as the platform from which the data originates and the parameter that was measured. Whenever possible, controlled vocabularies were used. Due to the heterogeneity of the data, including climate model results as well as long-tail biogeochemical campaign data, this is an ongoing process.The HCDC datasearch portal provides an example of the challenges and opportunities of combining data from distributed data sources through a single entry-point based on state-of-the-art web technologies. It can be used to discuss the challenges of re-using legacy solutions in a continually progressing research data infrastructure world.
Future socio-ecosystem productivity threatened by compound drought-heatwave events
Authors: Yin Jiabo , Gentine Pierre , Slater Louise , Gu Lei , Pokhrel Yadu , Guo Shenglian
Published: February 2023

Compound drought-heatwave (CDHW) events are one of the worst climatic stressors for global sustainable development. However, the physical mechanisms behind CDHW and their impacts on socio-ecosystem productivity remain poorly understood. Here, by combining satellite observations, field measurements and reanalysis, we show that terrestrial water storage and temperature are negatively coupled, likely driven by similar atmospheric conditions (e.g., water vapor deficit and energy demand). Using simulations from a large climate-hydrology model ensemble of 111 members, we demonstrate that the frequency of extreme CDHWs is projected to increase by ten-fold globally under the highest emissions scenario, along with a disproportionate negative impact on vegetation and socioeconomic productivity by the late 21st century. Limits on water availability are likely to play a more important role in constraining the terrestrial carbon sink than temperature extremes, and over 90% of the global population and GDP could be exposed to increasing CDHW risks in the future, with more severe impacts in poorer or rural areas. Our results provide crucial insights towards assessing and mitigating adverse effects of compound hazards on ecosystems and human well-being.
Silicic magmas, crystal mushes, granitic plutons and rhyolitic eruptions
Authors: Clemens John , Bryan Scott , Petford Nick
Published: February 2023

A crystallising magma must necessarily pass through a mushy (crystal-dominated) state before it fully solidifies. Similarly, partially melted magma source regions start out as solid-liquid mixtures, albeit with different initial conditions and physical behaviours to melt crystallisation. Thus, localised crystal mushes must be geologically commonplace. Here we examine the pervasive paradigm in which crystal mushes are thought of as the main sources of erupted silicic magmas. Combining geophysical, petrological, chemical and isotopic evidence, as well as theoretical considerations, we emphasise the following points.Models of plutonic rocks as mush cumulates left in magma reservoirs after extraction of fractionated and eruptible rhyolitic magmas are untenable. Compositions of rhyolites and granitic rocks show that, in general and even in well-constrained crustal sections, these are neither compositional equivalents nor compositional complements.
In rhyolitic rocks, apparent resorption textures in autocrysts and antecrysts should not necessarily be ascribed to mush heating events or percolative reactive flow of melt through mushes. Embayed and partially resorbed crystals in volcanic rocks, can also reflect rapid disequilibrium crystallisation and growth, partial resorption on near-adiabatic magma ascent or pre-eruption magma mingling/mixing. Likewise, the commonly monomineralic character of glomerocrysts shows that these cannot generally represent disaggregated crystal mushes.
The concept of rheologically locked crystal mush is not soundly based in mechanics. Under shear stress, a magma reservoir with 20 vol.% (and less) silicic melt can undergo rapid flow and melt segregation, and potentially collapse any mush column that might exist.
Geological mapping demonstrates that mafic floors to silicic plutons are uncommon, calling into question the idea of mush reactivation through heating by mafic magma influx.
An implication of the mush model is that most magma, mush and rock that is generated cannot be erupted, and the plutonic:volcanic ratio is probably rather greater than the 10:1 that is generally supposed. Thus, very large silicic eruptions (>1000 to 10,000 km3 in erupted volume) pose problems for mush models, in terms of the complementary mush volume that would be required.
We recommend that mush-based petrogenetic models be seriously reconsidered. Crystal mushes play a role, but this model should not be invoked to explain all volcanism. We present an internally consistent vision for silicic magma systems, underpinned by fundamental geological, petrological and mechanical observations and principles. This model obviates the need for ubiquitous, expedient mush zones or columns, and allows the crust to remain mechanically stable.
Extracting flood locations from news media data by the named entity recognition (NER) model to assess urban flood susceptibility
Authors: Fu Shengnan , Lyu Heng , Wang Ze , Hao Xin
Published: February 2023

Flood susceptibility assessment for identifying flood-prone areas plays a significant role in flood hazard mitigation. Machine learning is an optional assessment method because of its high objectivity and computational efficiency, but how to get enough and accurate information of historical flood locations to train the machine learning models has been a key problem. In recent years, news media data from both news websites and social media authentication accounts has emerged as a promising source for natural science studies. However, the application of news media data in urban flood susceptibility assessment is still inadequate. This study proposed an approach of three tasks to use news media data on this topic. Firstly, flood locations were extracted from news media data based on a named entity recognition (NER) model. Then, a frequency or distance-based data quality control method was employed to improve the representativeness of the extracted flooded locations. Finally, flood conditioning factors with information of historical flood locations were input into a Support Vector Machine (SVM) model for flood susceptibility assessment. We took the central city of Dalian, China, as a case study. The results show that there was no significant difference of a T-test between the distributions of most flood conditioning factors at the flood locations from the news media data and the official planning report. In the obtained flood susceptibility map, the high flood susceptibility areas got a recall of 90% compared with the high flood hazard areas in the planning report. Performing data quality control in the frequency-based method can improve the precision of the flood susceptibility map by up to 5%, while the distance-based method is ineffective. This study provides an example and offers the value of applying new data sources and modern deep learning techniques for urban flood management. 
Large-scale comparison of machine and statistical learning algorithms for blending gridded satellite and earth-observed precipitation data
Authors: Papacharalampous Georgia , Tyralis Hristos , Doulamis Anastasios , Doulamis Nikolaos
Published: February 2023

An established way for improving the accuracy of gridded satellite precipitation products is to “correct” them by exploiting ground-based precipitation measurements, together with machine and statistical learning algorithms. Such corrections are made in regression settings, where the ground-based measurements are the dependent variable and the satellite data are predictor variables. Comparisons of machine and statistical learning algorithms in the direction of obtaining the most useful precipitation datasets by performing such corrections are regularly conducted in the literature. Nonetheless, in most of these comparisons, a small number of machine and statistical learning algorithms are considered. Also, small geographical regions and limited time periods are examined. Thus, the results provided tend to be of local importance and to not offer more general guidance. To provide results that are generalizable, we compared eight state-of-the-art machine and statistical learning algorithms in correcting satellite precipitation data for the entire contiguous United States and for a 15-year period. We used monthly data from the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) gridded dataset and the Global Historical Climatology Network monthly database, version 2 (GHCNm). Our results suggest that extreme gradient boosting (XGBoost) and random forests are more accurate than the remaining algorithms, which can be ordered as follows from the best to the worst ones: Bayesian regularized feed-forward neural networks, multivariate adaptive polynomial splines (poly-MARS), gradient boosting machines (gbm), multivariate adaptive regression splines (MARS), feed-forward neural networks, linear regression.
Retrieval of snow layer and melt pond properties based on airborne hyperspectral imagery
Authors: Rosenburg Sophie , Lange Charlotte , Jäkel Evelyn , Schäfer Michael , Wendisch Manfred
Published: February 2023

The melting snow layer, as a composition of ice, liquid water, and air, supplies meltwater in the runoff phase inducing the melt pond formation. These melting processes of Arctic sea ice alter the surface reflection properties and thereby affect the energy budget. Such sea ice surface reflection properties were surveyed by airborne hyperspectral imagery within the framework of an Arctic field campaign performed in May/June 2017. A retrieval approach based on different absorption indices of pure ice and liquid water in the near infrared spectral range is applied to the campaign data retrieving the spatial distribution of snow layer liquid water fraction and effective radius of snow grains. For the same sceneries the melt pond depth was retrieved based on an existing approach that isolates the dependence of a melt pond reflectance spectrum on the pond depth by eliminating the reflection contribution of the pond ice bottom. The presented retrieval methods show the potential of airborne hyperspectral imagery to map the transition phase of the Arctic sea ice surface examining the snow layer composition and melt pond bathymetry.