bluuebunny/crossref_metadata_2025 huggingface dataset:
A new classification of the Arctic spring transition in the middle atmosphere
Authors: Matthias Vivien , Stober Gunter , Kozlovsky Alexander , Lester Mark , Belova Evgenia , Kero Johan
Published: March 2021

In the middle atmosphere, spanning the stratosphere and mesosphere, spring transition is the time period where the zonal circulation reverses from winter westerly to summer easterly which has a strong impact on the vertical wave propagation influencing the tropospheric and ionospheric variability. The spring transition can be rapid in form of a final sudden stratospheric warming (SSW, mainly dynamically driven) or slow (mainly radiatively driven) but also intermediate stages can occur. In most studies spring transitions are classified either by their timing of occurrence or by their vertical structure. However, all these studies focus exclusively on the stratosphere and can give only tendencies under which pre-winter conditions an early or late spring transition takes place and how it takes place. Here we classify the spring transitions regarding their vertical-temporal development beginning in January and spanning the whole middle atmosphere in the core region of the polar vortex. This leads to five classes where the timing of the SSW in the preceding winter and a downward propagating Northern Annular Mode (NAM) plays a crucial role. The results show distinctive differences between the five classes in the months before the spring transition especially in the mesosphere allowing a certain prediction for some of the five spring transition classes which would not be possible considering the stratosphere only.
The seasonal cycle of atmospheric CO2 in the southern hemisphere over the last ten years seen by GOSAT
Authors: Schömann Eva-Marie , Basu Sourish , Vardag Sanam N. , Haun Markus , Schreiner Lena , Butz André
Published: March 2021

In the southern hemisphere, the sparse coverage of in-situ CO2 measurements prevents a robust determination of regional carbon fluxes and leads to large uncertainties in inverse model results. Therefore, the extensive spatial coverage afforded by satellite CO2 measurements is especially valuable there. By analyzing satellite measurements, new insights on the carbon cycle can be derived and carbon cycle models can be validated for the southern hemisphere.

Here, we present a comparison of atmospheric CO2 data in Australia provided by the Greenhouse gases Observing SATellite (GOSAT) and the CarbonTracker (CT2019) inverse model from 2009 to 2018. We find that the seasonality of GOSAT CO2 is different from that of CarbonTracker across much of the southern hemisphere. This discrepancy follows a clear seasonal pattern with the largest difference of ~2ppm between October and December. We investigate the origin of the discrepancy by utilizing the CO2 components provided by CarbonTracker and different fire CO2 emission databases. Further, we conduct several sensitivity studies by assimilating GOSAT CO2 in the TM5-4DVar data assimilation system, and by transporting different surface fluxes through the TM5 transport model. Our results suggest that the underestimation of local and transported wildfire CO2 emissions could cause the observed discrepancy in the seasonality of column CO2 between GOSAT and inverse models such as CarbonTracker in the southern hemisphere.
Closing the global mean sea level budget from altimetry, GRACE/GRACE Follow-On and Argo data (2005-present)
Authors: Barnoud Anne , Cazenave Anny , Pfeffer Julia , Ablain Michaël , Guérou Adrien , Chen Jianli
Published: March 2021

Change in the global mean sea level (GMSL) is the sum of changes in the global mean steric sea level and global mean ocean mass. Over the 1993-2016 period, the GMSL budget was found to be closed, as shown by many independent studies. However, non-closure of the sea level budget after 2016 has been recently reported when using altimetry, Argo and GRACE/GRACE Follow-On data (Chen et al., GRL, 2020). This non-closure may result from errors in one or more components of the sea level budget (altimetry-based GMSL, Argo-based steric sea level or GRACE-based ocean mass). In this study, we investigated possible sources of errors affecting atlimetry and Argo data used to assess closure of the GMSL budget. Concerning altimetry data, we compared the wet tropospheric correction (WTC) applied to Jason-3 data (the reference satellite mission used for the GMSL computation since 2016) with that from the SARAL/AltiKa mission, and found no systematic bias between the radiometer measurements from these two missions. Besides, preliminary comparisons of GMSL trends (using the WTC ECMWF model) between different missions do not suggest discrepancies larger than 0.4 mm/yr over 2016-present. While further analyses are still needed, we find unlikely that non-closure of the sea level budget results from errors of the altimetry system. Concerning Argo data, since 2016, salinity data from different processing groups display strong discrepancies, likely due to instrumental problems and data editing issues. Good agreement is found between all available Argo-based thermosteric products. Given that the halosteric component should be negligible in global average, we re-examined the sea level budget since 2016 using only the thermosteric component and found significant improvement in the budget closure, although it is not yet fully closed. This suggests that the observed discrepancies in the Argo-based halosteric component largely contribute to the non-closure of the GMSL budget in the recent years.
Digitalisation and citizen participation - opportunities for integrated management of urban water infrastructure
Authors: Oberascher Martin , Rauch Wolfgang , Sitzenfrei Robert
Published: March 2021

In the field of urban water infrastructure (UWI), a system-wide management, that interacts with other infrastructure areas, is gaining importance. Additionally, new technologies based on the Internet of Things (IoT) concept, as part of smart city development, are rapidly emerging. This allows for new possibilities in the management of UWI. However, in literature, there is a lack of information about usable communication technology making it challenging to reproduce existing research.

To contribute to this ongoing development, the results of a detailed literature review are presented focusing on (smart) applications related to network-based UWI. Therefore, existing, and new applications of urban drainage and water distribution - including nature-based solutions - are analysed to provide a comprehensive analysis over required spatial and temporal resolution of measurement and control data for a cross-system view. To close the knowledge gap between UWI applications and usable (IoT) communication technology, a detailed framework is presented to identify suitable communication technologies based on spatial and temporal requirements for smart UWI operation. This framework can be used by researchers and stakeholders to choose a suitable communication technology based on their intended UWI applications, or vice versa, to indicate UWI applications, which are possible with an existing communication network.

The intersections with basic conditions of data communication (e.g., transmission range, data rate, reliability) reveal, that small-scale system parts (e.g., IoT-based micro storages, nature-based solutions) can be integrated into an overall controlled system by using state-of-the-art IoT technology in combination with citizen participation. However, monitoring and controlling networks in the field of UWI are based on battery-powered measurement devices due to underground and remote installation sites, and requires investment costs, too. Consequently, a balance between measurement equipment and effectiveness of the implemented applications is required to achieve economic and ecological sustainability
Variable preservation of tephra from the 1991 eruption of Volcán Hudson in small lakes: implications for reconstructing past eruption parameters
Authors: Streeter Richard , Cutler Nick , Lawson Ian
Published: March 2021

Volcanic ash (tephra) deposits are used to reconstruct past eruption parameters. The ways in which tephra deposits are modified between deposition and their long-term preservation in the stratigraphic archive are poorly understood. In particular, we don’t know if tephra layers preserved in lake sediments from small lakes accurately reflect the initial tephra fallout. We address this by re-surveying tephra deposits from the 1991 eruption of Volcán Hudson, Chile. We measured tephra thickness, mass-loading and grain-size distribution of tephra from multiple cores in six small (<0.2 km2) lakes at locations 76-110 km from the volcano and in areas of contrasting land cover and climate. We also measured tephra preservation in terrestrial sites within each lake catchment. These data were compared with measurements taken shortly (days to weeks) after the eruption to determine how the tephra deposits have changed in the 29 years since the eruption. Preservation is variable within and between lakes, and also varies with the vegetation cover at terrestrial sites adjacent to the lakes. Tephra thicknesses are broadly comparable to the original fallout, but the degree of similarity varied notably and is sensitive to preservation environment. These findings have implications for reconstructing eruption parameters from tephra deposits in small lakes, and where the fallout area crosses large environmental gradients and contrasting vegetation regimes.
Strip-like plasma bulges at lower-middle latitudes over a wide range of longitude during 8~9 September 2017 geomagnetic storm
Authors: Wan Xin , Zhong Jiahao , Xiong Chao
Published: March 2021

During the geomagnetic storm on 8~9 September 2017, a new kind of ionospheric irregularity is persistently captured in lower-middle latitudes at multiple local times, based on Swarm and DMSP satellites observations. This irregularity is observed as the conjugate strip-like bulge, which extends larger than 150° in longitude but only 1°~5° in latitude. The strip-like bulges can be categorized into sharp and blunt types depending on the sharpness of the density peaks. The blunt type is short-lived and appears earlier than the sharp type in the afternoon-sunset sector. The sharp type is long-lived and appears at all the observed local times. Both two types of strip-like bulges are dominated by the ion composition of the H+ /He+. This is the first evidence that the plasmaspheric particles are involved in forming the ionospheric structure at such low latitude. Moreover, the latitude/L-shell of the bulges decreased synchronously with the plasmaspheric compression. Also, these two types of strip-like bulges show different longitudinal dependencies controlled by the magnetic declination. We suggest that the combined effect from the plasmaspheric downwelling and disturbance neutral wind is responsible for the appearance of the strip-like bulges.
Ocean heat transport as a driver of sea ice extent in CMIP6 models
Authors: Aylmer Jake , Ferreira David , Feltham Daniel
Published: March 2021

Estimating long-term projections of sea ice extent is a key part of understanding the possible future climate state. This is hampered by uncertainties within and across comprehensive climate models, and the relative importance and nature of contributing factors are not fully understood. Here, we investigate the role of ocean and atmospheric forcing on sea ice on multidecadal time scales.

Pre-industrial control simulations of 19 CMIP6 models are analysed. Sea ice extent is negatively correlated with ocean heat transport (OHT), and positively correlated with atmospheric heat (moist-static energy) transport (AHT), in both hemispheres. In most models, increased OHT into the Arctic enhances surface fluxes in the Atlantic sector just south of the sea ice edge, which in turn increases the AHT convergence at higher latitudes. In the southern ocean, increased OHT directly increases the mean ocean–ice heat flux while AHT plays no direct role. Sensitivities of the sea ice cover to OHT are consistent with predictions from an idealised energy balance model (EBM), which is fitted to each model in turn. This shows that the sensitivities are constrained by atmospheric radiation parameters and the mean surface temperature response, with no explicit dependence on ocean parameters. These results are a step towards quantifying the effect of ocean biases on sea ice uncertainty in climate projections.
Comparison of wavelet and machine learning methods for regional drought prediction
Authors: Hinge Gilbert , Sharma Ashutosh
Published: March 2021

Droughts are considered as one of the most catastrophic natural disasters that affect humans and their surroundings at a larger spatial scale compared to other disasters. Rajasthan, one of India's semiarid states, is drought inclined and has experienced many drought events in the past. In this study, we evaluated different preprocessing and Machine Learning (ML) approaches for drought predictions in Rajasthan for a lead-time of up to 6 months. The Standardized Precipitation Index (SPI) was used as the drought quantifying measure to identify the drought events. SPI was calculated for 3, 6, and 12-month timescales over the last 115-year using monthly rainfall data at 119 grid stations.  ML techniques, namely Artificial Neural Network (ANN), Support Vector Regression (SVR), and Linear Regression (LR), were used to evaluate their accuracy in drought forecasting over different lead times. Furthermore, two data processing methods, namely the Wavelet Packet Transform (WPT) and Discrete Wavelet Transform (DWT), have also been used to enhance the aforementioned ML models' predictability. At the outset, the preprocessed SPI data from both the methods were used as inputs for LR, SVR, and ANN to form a hybrid model. The hybrid models' drought predictability for a different lead-time was evaluated and compared with the standalone ML models. The forecasting performance of all the models for all 119 grid points was assessed with three statistical indices: Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency (NSE). RMSE was used to select the optimal model parameters, such as the number of hidden neurons and the number of inputs in ANN, and the level of decomposition and mother wavelet in wavelet analysis.  Based on these measures, the coupled model showed better forecasting performance than the standalone ML models. The coupled WPT-ANN model shows superior predictability for most of the grid points than other coupled models and standalone models.  All models' performance improved as the timescale increased from 3 to 12 months for all the lead times. However, the model performance decreased as the lead time increased.  These findings indicate the necessity of processing the data before the application of any machine learning technique. The hybrid model's prediction performance also shows that it can be used for drought early warning systems in the state.
The benthic foraminiferal response to the mid-Maastrichtian event in the Maastrichtian-type area
Authors: Vancoppenolle Iris , Vellekoop Johan , Doubrawa Monika , Kaskes Pim , Sinnesael Matthias , Jagt John , Claeys Philippe , Speijer Robert P.
Published: March 2021

The mid-Maastrichtian event (MME), ~69 Ma, represents a global negative δ13C excursion which is linked to the extinction of inoceramid bivalves and latitudinal migration of planktonic foraminifera. While the actual extinction of inoceramids was diachronous across the globe, the decline of this important fossil group is generally linked to environmental changes across the mid-Maastrichtian interval. The MME is potentially related to changes in oceanic circulation. While the MME, and associated decline of inoceramids, has been recorded from a variety of deep-sea sites, little is known about the MME signature in shallow epicontinental environments.

Recently, the MME has been recorded for the first time from the type-Maastrichtian, in the Maastricht-Liège region (The Netherlands and Belgium), in newly generated bulk carbonate carbon isotope records from the Hallembaye quarry (NE Belgium) and former ENCI quarry (SE Netherlands). These quarries are approximately 8 km apart. The type-Maastrichtian succession was deposited in a shallow subtropical sea during the Late Cretaceous. As the stratigraphic position of the MME is now constrained in the type-Maastrichtian record, this succession presents an interesting opportunity for studying the signature of this event in a relatively shallow epicontinental basin. Therefore, we are generating high-resolution benthic foraminiferal assemblage data and species-specific carbon and oxygen stable isotope records across the MME interval at these two quarries, in order to unravel biotic and environmental expressions of the MME in the Maastrichtian type area. This is done using the high-resolution sample set acquired in the context of the Maastrichtian Geoheritage Project. Our preliminary data show a distinctive acme of the benthic foraminifer Cuneus trigona in the interval that roughly that corresponds to the MME, potentially caused by a change in quality of the organic matter that reached the sea bottom, highlighting local environmental and oceanographic perturbations across this event.
The role of land cover, land use, and atmospheric transport for the mismatch of flowering and atmospheric pollen seasonality
Authors: Menzel Annette , Yuan Ye
Published: March 2021

Aeroallergens contribute a major climate change impact on human health since warming favours the production and advances the release of plant pollen. This goes in line with a widely observed advance of flowering in response to increasing temperatures. However, documented plant phenological changes vary with species traits, seasons, and sites. Nevertheless, the start and end of flowering dates are known to build a solid baseline for assessing the spatial and temporal patterns in pollen calendars. A closer look at the match/mismatch of flowering and start of pollen season dates reveals considerable differences which may be also indirectly linked to climate change. In this talk, we will present three perspectives related to (1) grassland land use, cutting regimes and agri-environment measures (AEM), (2) post-season pollen transport of an alpine Alnus species, as well as (3) a first climatology of pre-season long-range pollen transport to Bavaria. These selected examples underline the prominent role of land use/land cover (LULC) and pollen transport besides direct temperature mediated climate change effects on flowering for regional pollen calendars.
The potential of carbon dioxide removal through enhanced weathering of basalt on agricultural land in Austria
Authors: Rinder Thomas , von Hagke Christoph
Published: March 2021

Enhanced weathering through basalt application on agricultural land represents a proposed strategy for the removal of carbon dioxide from the atmosphere. Co-benefits related to soil health, resilience and crop yield make basalt excellently suited as a sustainably technology for GHG mitigation in agriculture. It has been shown that enhanced weathering is principally feasible on a global scale, but it remains unclear whether it can be implemented on a local level. With this in mind, we estimate the potential for CO2 removal through a case study for Austria. Scenarios are estimated for three different particle size distributions (< 100 µm, < 10 µm and < 1 µm). We find that transport related emissions may cancel out any drawdown if grain sizes (< 100 μm) are used. However, under optimal transport conditions the large-scale application of particles with a diameter < 10 μm may remove about 2% of Austria's annual Greenhouse gas emissions while at the same time supplying important plant nutrients. We discuss challenges towards this goal, including the enormous amounts of basalt needed and the energy requirement related to grinding, as well as uncertainties related to actual field weathering rates. Those uncertainties hinder the precise quantification of CO2 drawdown as of now. While enhanced weathering remains a promising path for climate change mitigation, further research at laboratory and field scale is required to put this technology to optimal use. 
Atlantic equatorial deep jets in Argo float data
Authors: Bastin Swantje , Claus Martin , Brandt Peter , Greatbatch Richard J.
Published: March 2021

Equatorial deep jets (EDJ) are strong zonal currents in the deep tropical oceans that alternate in direction with depth and
time. In the Atlantic below the thermocline, they are the dominant variability on interannual timescales. They propagate
energy upwards and are suggested to impact surface climate variables on interannual timescales. They are also
important for the distribution of tracer in the mid-depth tropical ocean, for example by enhanced oxygen ventilation of
the eastern deep oxygen minimum zones, both through advection by the EDJ themselves and because the EDJ
nonlinearly drive time mean flow. Observations of equatorial deep jets are available but scarce, given the EDJs’ location
at depth and their long periodicity of several years. In the last few years, Argo floats have added a significant amount of
measurements at intermediate depth. We therefore perfomed a new EDJ scale analysis based on Argo float
measurements, the results of which we show here. At 1000 m depth, very weak or no EDJ signals can be detected in the
Indian and Pacific Oceans. In the Atlantic, however, the EDJ signal is strong at 1000 m depth, allowing us to obtain
good estimates of their frequency, amplitude, phase, zonal wavelength, and meridional structure.
Sensitivity of simulated oxygen isotopes in ice cores and speleothems to Last Glacial Maximum surface conditions
Authors: Paul André , Cauquoin Alexandre , Mulitza Stefan , Tharammal Thejna , Werner Martin
Published: March 2021

In simulations of the climate during the Last Glacial Maximum (LGM), we employ two different isotope-enabled atmospheric general circulation models (NCAR iCAM3 and MPI ECHAM6-wiso) and use simulated (by coupled climate models) as well as reconstructed (from a new global climatology of the ocean surface duing the LGM, GLOMAP) surface conditions.

The resulting atmospheric fields reflect the more pronounced structure and gradients in the reconstructions, for example, the precipitation is more depleted in oxygen-18 in the high latitudes and more enriched in low latitudes, especially in the tropical convective regions over the maritime continent in the equatorial Pacific and Indian Oceans and over the equatorial Atlantic Ocean. Furthermore, at the sites of ice cores and speleothems, the model-data fit improves in terms of the coefficients of determination and root-mean square errors.

In additional sensitivity experiments, we also use the climatologies by Annan and Hargreaves (2013) and Tierney et al. (2020) and consider the impact of changes in reconstructed sea-ice extent and the global-mean sea-surface temperature.

Our findings imply that the correct simulation or reconstruction of patterns and gradients in sea-surface conditions are crucial for a successful comparison to oxygen-isotope data from ice cores and speleothems.
Contribution of remote sensing and auxiliary variables in the study of the evolution of periods of droughts
Authors: Farhani Nesrine , Boulet Gilles , Carreau Julie , Kassouk Zeineb , Le Page Michel , Lili Chabaane Zohra , Zitouna Rim
Published: March 2021

In semi-arid areas, plant water use and plant water stress can be derived over large
areas from remotely sensed evapotranspiration estimates. Those can help us to monitor the
impact of drought on the agro- and ecosystems. Both variables can be simulated by a dual
source energy balance model that relies on meteorological variables (air temperature, relative
humidity, wind speed and global radiation) and remote sensing data (surface temperature,
NDVI, albedo and LAI). Surface temperature acquired in the Thermal InfraRed (TIR) domain
is particularly informative for monitoring agrosystem health and adjusting irrigation
requirements. However, available meteorological observations period may often be
insufficient to account for the variability present in the study area. Statistical downscaling
methods applied to reanalysis data can serve to generate surrogate series of meteorological
variables that either fill the gaps in the observation period or extend the observation period in
the past. For this aim, a stochastic weather generator (SWG) is adapted in order to compute
temporal extension of multiple meteorological variables. This surrogate series is then used to
constrain the dual-source model Soil Plant Atmosphere and Remote Evapotranspiration
(SPARSE). Stress index anomalies retrieved from SPARSE are then compared to anomalies in
other wave lengths in order to assess their capacity to detect incipient water stress and early
droughts at the kilometer resolution. Those are the root zone soil moisture at low resolution
derived from the microwave domain, and active vegetation fraction cover deduced from
NDVI time series.
Subduction zone seismo-dynamics: how to bridge the gap between long-term subduction dynamics and megathrust seismicity?
Authors: Beall Adam , Capitanio Fabio A. , Fagereng Ake , van Dinther Ylona
Published: March 2021

The largest and most devastating earthquakes on Earth occur along subduction zones. Here, long-term plate motions are accommodated in cycles of strain accumulation and release. Episodic strain release occurs by mechanisms ranging from rapid earthquakes to slow-slip and quasi-static creep along the plate interface. Slip styles can vary between and within subduction zones, though it is unclear what controls margin-scale variability. Current approaches to seismo-tectonics primarily relate the stress state and seismogenesis at subduction margins to interface material properties and plate kinematics, constrained by recorded seismic slip, GPS motions and integrated strain. At larger spatio-temporal scales, significant progress has been made towards the understanding of subduction dynamics and emerging self-consistent plate motions, tectonics and stress coupling at plate margins. The margin stress state is ultimately linked to the force balance arising from interactions between the slab, mantle flow and upper plate. These mantle and lithosphere dynamics are thus expected to govern the tectonic regimes under which seismicity occurs. It remains unclear how these longer- and shorter-term perspectives can be reconciled. We review the aspects of large-scale subduction dynamics that control tectonic loading at plate margins, discuss possible influences on the stress state of the plate interface, and summarise recent advances in integrating the earthquake cycle and large-scale dynamics. It is plausible that variations in large-scale subduction dynamics could systematically influence seismicity, though it remains unclear to what degree this interplay occurs directly through the plate interface stress state and/or indirectly, corresponding to variation of other subduction zone characteristics. While further constraints of the geodynamic controls on the nature of the plate interface and their incorporation into probabilistic earthquake models is required, their ongoing development holds promise for an improved understanding of the global variation of large earthquake occurrence and their associated risk.
Diverse dynamical response to orographic gravity wave drag hotspots - a zonal mean perspective
Authors: Šácha Petr , Kuchař Aleš , Eichinger Roland , Pišoft Petr , Jacobi Christoph , Rieder Harald
Published: March 2021

In the extratropical atmosphere, Rossby waves (RWs) and internal gravity waves (GWs) propagating from the troposphere mediate a coupling with the middle atmosphere by influencing the dynamics herein. In the current generation chemistry-climate models (CCMs), RW effects are well resolved while GW effects have to be parameterized. Here, we analyze orographic GW (OGW) interaction with resolved dynamics in a comprehensive CCM on the time scale of days. For this, we apply a recently developed method of strong OGW drag event composites for the three strongest northern hemisphere OGW hotspots. We show that locally-strong OGW events considerably alter the properties of resolved wave propagation into the middle atmosphere, which subsequently influences zonal winds and RW transience. Our results demonstrate that the influence of OGWs is critically dependent on the hotspot region, which underlines the OGW-resolved dynamics interaction being a two-way process.
Reducing the risk for contamination of river bank filtration systems using inverse modelling and anthopogenic traces
Authors: Marazuela Miguel Angel , Herrera Paulo , Erlmeier Klaus , Brünjes Robert , Brunner Philip , Hofmann Thilo
Published: March 2021

Many drinking water systems worldwide are based on river bank filtration. From a quantitative point of view river bank filtration systems are highly reliable because of the high permeability of alluvial aquifers linked to high production rates. However, there might be an increased risk of contamination because of the short residence time between the river and the production well, especially during flood events.

Flood events change the river-aquifer hydraulic interactions and may increase infiltration rates (e.g., due to an increased hydraulic head, larger river infiltration widths, or erosion of a siltation layer). This leads to changes in groundwater flow paths and production wells might abstract water with a shorter residence time and lower quality. Groundwater quality may degrade during flood events due to the presence of undesirable chemicals (e.g., wastes water treatment plant overflow) and the occurrence of faecal indicator bacteria such as E.Coli.

Groundwater modelling can assist in developing strategies to protect river bank filtration from such undesired contamination by predicting optimal operation conditions. The key impediment of this approach is significant uncertainties in subsurface properties and the associated uncertainties of the groundwater flow paths. To reduce uncertainties in model predictions, anthropogenic tracers including the MRI contrast agent gadolinium and artificial sweeteners were used in this study. They revealed sources and flow patterns, and have been used to derive mixing ratios representing different temporal and spatial scales. Including anthropogenic tracers into the objective function of the calibration process also lead to more accurate estimation of groundwater flow paths. This was critical to predict the best water works operation strategy during flood events.
Machine learning classifiers for detecting and classifying major explosions and paroxysms at Stromboli volcano (Italy) using radar and optical satellite imagery
Authors: Del Negro Ciro , Corradino Claudia , Amato Eleonora , Torrisi Federica , Calvari Sonia
Published: March 2021

The persistent explosive activity of Stromboli is characterized by several hundred of moderate-intensity events per day. These explosions eject pyroclastic fragments to the height of some tens of meters, which fall a short distance from the summit vents. Occasionally, major explosions eject pyroclastic material to more than a few hundred meters high, which can fall outside the crater terrace on the area visited by tourists. The frequency of these phenomena is variable, with an average of 2 events per year. Paroxysms, violent explosions that produce eruptive columns more than 3 km high and are often associated with pyroclastic flows, can also occur at Stromboli. Ballistic blocks associated with these explosions can reach up to 4 m in diameter and fall on the hinabited areas. Paroxysms are rare (5 events in the last 20 years) and their occurrence frequency varies over time. Nevertheless, major explosions and paroxysms represent the main danger to visitors and inhabitants of the Stromboli Island. Here, we propose a novel approach to detect and classify the type of explosive activity occurring on Stromboli volcano by combining radar and optical satellite imagery with machine learning algorithms. In particular, we considered the plume height, the summit area temperature, and the area affected by large ballistic projectiles as the discriminant factors to distinguish between ordinary activity, major explosions and paroxysms. These factors are retrieved from both radar (Sentinel-1-GRD) and multi-spectral (Landsat-MSI and TIR) satellite images and fed to a machine learning classifier. A retrospective analysis is conducted investigating the main explosive events that have occurred since 1983. This algorithm is based on the in the Google Earth Engine (GEE), which is a cloud computing platform for environmental data analysis from local to planetary scales, with fast access and processing of satellite data from different missions.
Imaging the Plasmasphere and Topside Ionosphere during Geomagnetic Storms based on a Tomographic Algorithm
Authors: Prol Fabricio , Hoque Mainul
Published: March 2021

In this study, TEC measurements from METOP (Meteorological Operational) satellites are used together with a tomographic algorithm to estimate electron density distributions during geomagnetic storm events. The proposed method is applied during four geomagnetic storms to check the tomographic capabilities for space weather monitoring. The developed method was capable to successfully capture and reconstruct well-known enhancement and decrease of electron density during the geomagnetic storms. The comparison with in-situ electron densities from DMSP (Defense Meteorological Satellite Program) satellites has shown an improvement around 11% and a better plasma description compared to the background. Our study also reveals that the plasmasphere TEC contribution to ground-based TEC may vary 10 to 60% during geomagnetic storms, and the contribution tends to reduce during the storm-recovery phase.
The Seismica initiative: a community-led Diamond Open Access journal for seismological research
Authors: van den Ende Martijn , Bruhat Lucile , Funning Gareth , Gabriel Alice-Agnes , Hicks Stephen , Jolivet Romain , Lecocq Thomas , Rowe Christie , Seismological Community The
Published: March 2021

On 24 November 2020, the Springer Nature publishing group announced the introduction of Open Access (OA) journals in Nature and its sibling journals. The corresponding OA publication fee (charged directly to the authors) was set to €9,500/$11,390/£8,290, an amount that may be well out of reach for researchers with limited financial means. This is especially a problem for researchers in developing countries, and for early-career researchers on small, personal fellowships. Funding agencies often demand that research be published under an OA license, forcing authors to accept the high publication fees.

The high cost of these and similar OA fees for other Earth science journals prompted a discussion among the seismological community on Twitter, during which the idea was raised to start a free-to-publish, free-to-read journal for seismological research. The concept of Diamond Open Access was previously adopted by Volcanica (www.jvolcanica.org) for volcanological research, providing a precedent and directives for similar initiatives (like Seismica, but also Tektonika for the structural geology community). Following the community discussion on Slack with over 100 participants, a small "task force" was formed to investigate in detail the possibility of starting a Diamond OA seismology journal, taking Volcanica as a model. In this contribution, we report the progress that has been made by the task force and the seismological community in the conceptualisation of the journal, and the steps that remain to be taken. Once the initiation of the journal is completed, Seismica will offer a platform for researchers to publish and access peer-reviewed work with no financial barriers, promoting seismological research in an inclusive manner. We invite all interested members of the seismological and earthquake community to participate in the discussions and development of this OA journal, by contacting the authors listed on this abstract.
Managing Geophysics datasets: Challenges and perspectives from the UK Polar Data Centre
Authors: Fremand Alice
Published: March 2021

Today, open data policies are better understood by scientists and writing a data management plan is part of every Natural Environment Research Council (NERC) project submission. But that means that scientists are expecting more and more from their data publication or data requests: they want interactive maps, they want more complex data systems, they want to query data and publish them rapidly.

At the UK Polar Data Centre (PDC, https://www.bas.ac.uk/data/uk-pdc/), the datasets are very diverse, reflecting the multidisciplinary nature of polar science. Geophysics datasets include bathymetry, aerogravity, aeromagnetics and airborne radar depth soundings. Encouraging reuse and increasing the value of data is at the core of PDC’s mission. Data published by the PDC are used in a large variety of scientific research projects internationally. For instance, the significant datasets from seabed multibeam coverage of the Southern Ocean enables the British Antarctic Survey to be a major contributor to multiple projects such as International Bathymetric Chart of the Southern Ocean (IBCSO) and Seabed 2030. The wide coverage of airborne radar echo sounding over Antarctica is crucial for the SCAR BEDMAP3 project which aims to produce new map of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.

Over the last year, procedures to preserve, archive and distribute these data have been revised and updated to comply with the requirements of CoreTrustSeal. But we are still looking for new technologies, tools, open-source software that will help us bring interactivity to our datasets and reach the expectations of scientists.
On the speed and numerical stability of ice-dynamics approximations
Authors: Robinson Alexander , Lipscomb William , Goldberg Daniel , Alvarez-Solas Jorge
Published: March 2021

The Stokes solution to ice dynamics is computationally expensive, and in many cases unnecessary. Many approximations have been developed that reduce the complexity of the problem and thus reduce computational cost. Most approximations can generally be tuned to give reasonable solutions to ice-dynamics problems, depending on the domain and scale being simulated. However, the inherent numerical stability of time-stepping with different solvers has not been studied in detail. Here we investigate how different approximations lead to limits on the maximum timestep in mass conservation calculations for both idealized and realistic geometries. The ice-sheet models Yelmo and CISM are used to compare the following approximations: the shallow-ice approximation (SIA), the shallow-shelf approximation (SSA), the SIA+SSA approximation (Hybrid) and two variants of the L1L2 solver, namely one that reduces to SIA in the case of no-sliding (dubbed L1L2-SIA here) and the so-called depth-integrated viscosity approximation (DIVA). We find that these approaches vary significantly with respect to numerical stability. The extreme dependence on the local surface gradient of the SIA-based approximations (SIA, Hybrid, L1L2-SIA) leads to an amplified local velocity response and greater potential for instability, especially as grid resolution increases. In contrast, the SSA and DIVA approximations allow for longer time steps, because numerical oscillations in ice thickness are damped with increasing resolution. Given its high fidelity to the Stokes solution and its favorable stability properties, we demonstrate the strong case for using the DIVA approximation in many contexts.
Enhanced levels of nitrous acid during daytime derived from MAX-DOAS measurements during the AQABA campaign in late summer 2017
Authors: Dörner Steffen , Donner Sebastian , Behrens Lisa , Beirle Steffen , Osipov Sergey , Wagner Thomas
Published: March 2021

During the Air Quality and Climate Change in the Arabian Basin (AQABA) campaign a MAX-DOAS instrument was set up on board of the Kommandor Iona. The ship route covered a variety of regions with different atmospheric compositions: Clean air in the Mediterranean and the Arabian Sea, anthropogenic air pollution near the oil fields in the Arabian Gulf or in areas of dense ship traffic like the Suez Channel or the dust clouds of the nearby deserts in the Red sea. The measured spectra in the UV/VIS spectral range (302 to 467nm) provide sufficient information for the retrieval of aerosol and trace gas profiles. In this study, we focus on evidences of direct nitrous acid emission sources in harbor areas around Jeddah and Kuwait. Since HONO daytime chemistry is debated in recent literature and missing sources are being discussed, we compared the results of the MAX DOAS measurements to WRF-Chem model output in order to identify potential daytime sources in maritime/harbor regions.
Data-based attribution of changes in flood quantiles across Europe between 1960 and 2010
Authors: Bertola Miriam , Viglione Alberto , Vorogushyn Sergiy , Lun David , Merz Bruno , Blöschl Günter
Published: March 2021

Changes in European floods during past decades have been analysed and detected by several studies. These studies typically focused on the mean flood behaviour, without distinguishing small and large floods. In this work, we investigate the causes of the detected flood trends across Europe over five decades (1960-2010), as a function of the return period. We adopt a regional non-stationary flood frequency approach to attribute observed flood changes to potential drivers, used as covariates of the parameters of the regional probability distribution of floods. The elasticities of floods with respect to the drivers and the regional contributions of the drivers to changes in flood quantiles associated with small and large return periods (i.e. 2-year and 100-year floods, respectively) are estimated by Bayesian inference, with prior information on the elasticity parameters obtained from expert knowledge and the literature. The data-based attribution approach is applied to annual maximum flood discharge seires from 2370 hydrometric stations in Europe. Extreme precipitation, antecedent soil moisture and snowmelt are the potential drivers considered. Results show that extreme precipitation mainly contributes to positive flood changes in North-western Europe. Both antecedent soil moisture and extreme precipitation contribute to negative flood changes in Southern Europe, with relative contributions varying with the return period. Antecedent soil moisture contributes the most to changes in small floods (i.e. T=2-10 years), while the two drivers contribute with comparable magnitude to changes in more extreme events. In eastern Europe, snowmelt clearly drives negative changes in both small and large floods.
The potential of data driven approaches for quantifying hydrological extremes
Authors: Hauswirth Sandra Margrit , Bierkens Marc , Beijk Vincent , Wanders Niko
Published: March 2021

Recent droughts have shown that national water systems are facing increasing challenges over the last few years. As such, the Netherlands has seen increasing needs to adapt their water management in order to improve their preparedness for current and future drought events. Ideally, the necessary information needed for operational water management decisions should be readily available ahead in time and/or computed in a flexible and efficient way to ensure the various management actions. In this study we show that in addition to the physically based hydrological models, the upcoming and promising trend of incorporating machine learning (ML) in hydrology can increase the information produced to support national and operational water management.

To investigate the potential of ML for this case, we assessed 5 different ML methods to predict the following hydrological variables relevant for water management at a national scale: timeseries of discharge, groundwater levels, surface water levels and surface water temperatures. We developed a unified workflow for all the methods and variables of interest. As inputs, we only used a limited set of hydro-meteorological variables and general water management policies that are readily available on a daily basis and that can be used when the ML methods are used in seasonal forecasting mode.

We show that all methods have a good performance, with a normalized RMSE ranging between 0.0 and 0.4, and Random Forest outperforming other methods. This performance remains stable for low flows, where we observe that complex ML methods outperform simpler algorithms. The addition of water management in the ML routine increases overall performance, although limited. Finally, we observe that locations further upstream show a better performance due to the limited water management influence and close proximity to input observations.

Our study shows that ML has potential in predicting different hydrological variables at various locations at a national scale with only a simple input data set of 5 meteorological and hydrological variables. We additionally were able to capture and incorporate water management information in our analysis, creating a base for future experiments where a combination of seasonal forecasting and scenario analysis might reveal ML-informed mitigation strategies. As such, our approach may improve the preparedness of the national water system of the Netherlands for future drought events.
Challenges and opportunities of remote sensing for monitoring biodiversity change
Authors: Timmermans Joris , Kissling Daniel
Published: March 2021

Biodiversity is rapidly declining and monitoring biodiversity change is thus of key importance to prevent the destabilization of ecosystems and their services. A key component of monitoring biodiversity change is the development of Essential Biodiversity Variables (EBVs) which facilitate the harmonization and standardization of raw data from disparate sources. In this context, consistent and adequate geospatial information needs to be available to ecologists and policymakers around the world, even for countries in which comprehensive in-situ biodiversity measurements cannot be taken on a regular basis. Satellite remote sensing (SRS) currently represents the only tool which allows to acquiree spatially contiguous and temporally replicated observations for monitoring biodiversity over continental or (near-)global spatial extents. Observations from SRS already provide a wealth of information on the distribution, structure and functioning of ecosystems, but user requirements of ecologists and policymakers have not been systematically quantified for allowing the development of roadmaps by SRS experts.

In response, we performed a top-down user requirement analysis combined with a bottom-up technical review to highlight (i) how currently available remote sensing products can contribute to biodiversity monitoring, and (ii) which immature SRS products could be prioritized for further development. We performed a systematic review of the Post2020 goals (for 2050) and biodiversity targets (for 2030) of the Convention on Biological Diversity (CBD) and their corresponding biodiversity indicators. Subsequently we evaluated SRS products according to relevance (to biodiversity indicators), (im)maturity, feasibility, and suitability for provisioning user-adequate spatio-temporal information. We found that currently existing CBD-relevant biodiversity indicators mainly use EBV-related information on ecosystem structure and distribution (e.g. available from remote sensing products of landcover and Leaf Area Index, LAI) or on species populations (predominantly acquired from in-situ biodiversity measurements because current SRS products are too limited in the spatio-temporal resolutions of their sensors). Moreover, only few biodiversity indicators derived from SRS currently focus on species traits or community composition EBVs, as both the identification of individual species and the quantification of species traits such as LAI and foliar nitrogen, phosphorus, kalium and chlorophyll content remain challenging. We outline how further advances in data-science techniques (e.g. merging SRS observations of high spectral and high spatial resolution) provide tremendous opportunities for advancing community composition and species-focused EBVs for global biodiversity monitoring.