bluuebunny/crossref_metadata_2025 huggingface dataset:
Building the Foundations for Open Applied Earth System Science in ENVRI-FAIR
Authors: Asmi Ari , Franz Daniela , Petzold Andreas
Published: March 2020

The EU project ENVRI-FAIR builds on the Environmental Research Infrastructure (ENVRI) community that includes principal European producers and providers of environmental research data and research services. The ENVRI community integrates the four subdomains of the Earth system - Atmosphere, Ocean, Solid Earth, and Biodiversity/Terrestrial Ecosystems. The environmental research infrastructures (RI) contributing to ENVRI-FAIR have developed comprehensive expertise in their fields of research, but their integration across the boundaries of applied subdomain science is still not fully developed. However, this integration is critical for improving our current understanding of the major challenges to our planet such as climate change and its impacts on the whole Earth system, our ability to respond and predict natural hazards, and our understanding and preventing of ecosystem loss.

 

ENVRI-FAIR targets the development and implementation of the technical framework and policy solutions to make subdomain boundaries irrelevant for environmental scientists, and prepare Earth system science for the new paradigm of Open Science. Harmonization and standardization activities across disciplines together with the implementation of joint data management and access structures at RI level facilitate the strategic coordination of observation systems required for truly interdisciplinary science. ENVRI-FAIR will finally create an open access hub for environmental data and services provided by the contributing environmental RIs, utilizing the European Open Science Cloud (EOSC) as Europe´s answer to the transition to Open Science.

 
Assessment of the CMEMS global biogeochemical forecasting operational system, with assimilation of Ocean Colour data
Authors: Lamouroux Julien , Mignot Alexandre , Perruche Coralie , Ruggiero Giovanni , Paul Julien , Testut Charles-Emmanuel , Lellouche Jean-Michel , Drillet Yann
Published: March 2020

The operational production of data-assimilated biogeochemical state of the ocean is one of the challenging core projects of the Copernicus Marine Environment Monitoring Service (hereafter CMEMS). In that framework, Mercator Ocean International is in charge of improving the realism of its global 1⁄4° coupled physical-biogeochemical simulations, analyses and re‐analyses, and to develop an effective capacity to routinely estimate the biogeochemical state of the ocean, including, amongst others, the implementation of biogeochemical data assimilation. Primary objectives are to enhance the time representation of the seasonal cycle in the real time and reanalysis systems, and to provide a better control of the production in the equatorial regions.

In that framework, Mercator Ocean International has successfully updated its global biogeochemical analysis and forecasting system with an Ocean Color data assimilation capability. In this system, successfully commissioned in September 2019, the biogeochemical model (NEMO/PISCES) is offline coupled with the dynamical ocean (1/12° coarsened to 1/4° resolution) from the CMEMS global physical analysis and forecasting operational system (PSY4), at a daily frequency, and benefits from the assimilation of satellite (SSH-SST-SIC) and in situ physical data. Nevertheless, a biogeochemical climatological damping is activated in the biogeochemical model in order to mitigate the impact of some misconstrained processes (vertical velocities) from this physical data-assimilated forcing (under investigation). The dedicated assimilation of biogeochemical data relies on a simplified version of the SEEK filter, where the forecast error covariances are built from a fixed-basis - but seasonally variable - ensemble of anomalies computed from a multi-year numerical experiment (without biogeochemical data assimilation) with respect to a running mean. Regarding Ocean Colour observations, the system relies, as a first step, on the CMEMS Global Ocean surface chlorophyll concentration products, delivered in NRT.

The objective of this presentation is thus to provide (1) a short description of the implementation of the aforementioned data assimilation methodology in the forecasting system; (2) a synthesis of the assessment of this global biogeochemical forecasting system, by cross-comparing the assimilated solution with various datasets, both spatial (Ocean Colour) and in situ (BGC-Argo, GLODAP), and (3) a synthetic overview of the impact/benefit of the assimilation of the Ocean Colour data.
The global statistical distribution of time intervals between consecutive earthquakes
Authors: González Álvaro , Serra Isabel , Corral Álvaro
Published: March 2020

Earthquakes cluster in time in a tighter way than in a Poisson process, in which events would be independent from each other and from when each one occurred. This tight clustering should be considered for forecasting the probability of ocurrence of earthquakes in a time period.

Nevertheless, the standard analysis of temporal earthquake occurrence usually proceeds by “declustering” the earthquake time series, trying to identify aftershocks or other triggered events and then pruning them from the sample, leaving only the supposedly independent events. This procedure attempts to artificially make the process Poissonian-like (so that the probability of the next earthquake is forced to be constant in time).

Since there is not a unique way of identifying triggered earthquakes, this removal is subjective to some degree (it involves lack of knowledge about the process, that is, epistemic uncertainty). Such a method also reduces the sample itself, reducing the power of any statistical inference made with it (in other words, with fewer events it is more difficult to distinguish which model best fits the data).

An example of this issue is the debate on whether the recent surge of great earthquakes (magnitude 8 or larger) since 2004 is random or not. If they were Poissonian, the distribution of time intervals between them should be exponential. The answer may depend on whether triggered events are artificially removed from the sample or not.

In this research, we explore in a comprehensive way the statistical distribution of time intervals between consecutive earthquakes worldwide. We use a complete earthquake catalogue, and do not attempt to separate triggered from independent events.

We consider different magnitude thresholds, and for each of them test which statistical distribution (such as Weibull, gamma or exponential) best fits the data. This enables us to quantitatively assess whether there is a universal distribution or, on the contrary, if it depends on the magnitude range considered. Also, we test whether Poissonian occurrence can be rejected for the whole series of the largest earthquakes.

Finally, we show how this distribution, calibrated for each magnitude range, can be used for calculating probabilities of earthquake occurrence in a time period of interest, in a more realistic way than typically achieved.
Field surveys and numerical modeling of the December 2018 Anak Krakatau volcanic tsunami
Authors: Heidarzadeh Mohammad , Sulastya Putra Purna , Muhari Abdul , Hari Nugroho Septriono
Published: March 2020

We report results of field surveys and numerical modeling of the tsunami generated by the Anak Krakatau volcano eruption on 22 December 2018. We conducted two sets of field surveys of the coastal areas destroyed by the Anak Krakatau tsunami in 26-30 December 2018 and 4-10 January 2020. Field surveys provided information about the maximum tsunami height as well as the most damaged area. The maximum tsunami height was up to 13 m. Most locations registered a wave height of 3-4 m. Tsunami inundation was limited to approximately 100 m. For modeling, we considered 12 source models and conducted numerical modeling. The scenarios have source dimensions of 1.5–4 km and initial tsunami amplitudes of 10–200 m. By comparing observed and simulated waveforms, we constrained the tsunami source dimension and initial amplitude in the ranges of 1.5–2.5 km and 100–150 m, respectively. The best source model involves potential energy of 7.14 × 1013–1.05 × 1014 J which is equivalent to an earthquake of magnitude 6.0–6.1.
Effects of sea surface temperature on distributions of two tropical tunas under the shifts of climate periodicity
Authors: Hsiao Yi-Ting , Lo Min-Hui , Wang Hui-Yu
Published: March 2020

   Tunas provide an important marine resource for the countries that surround the Pacific Ocean. Under climate change, climate models project an increasing frequency of central Pacific El Niño/Southern Oscillation events but a decreasing frequency of eastern Pacific El Niño/Southern Oscillation events, and may cause sea temperature rising in the central western Pacific relative to the eastern Pacific region and leading to corresponding changes in biological productivity, in turn influencing early life stage of tunas. Consequently, it is crucial to investigate how such climatic periodicity will impact the distribution and abundance of tunas.
   Here, yellowfin and albacore tunas are selected as our study species. Yellowfin tuna prefer warmer environments and have smaller body size and younger age-at-maturation (1 year) compared to albacore tunas (mature in 2 years). We use the spatially-explicit (5° grids) longline catch-and-effort data across 20°N~20°S and105°E~75°W,1970~2015, from Inter American Tropical Tuna Commission (IATTC) and Western & Central Pacific Fisheries Commission (WCPFC). We analyze the spatial and inter-annual variation in the catch-per-unit-effort for the two tunas with respect to changes in sea surface temperature in the central Pacific El Niño/Southern Oscillation events vs. the eastern Pacific El Niño/Southern Oscillation events. To investigate whether the distribution of tunas change under the central Pacific El Niño/Southern Oscillation events and the eastern Pacific El Niño/Southern Oscillation events will greatly help fisheries management and sustainable development of marine resources. 
Establishing a Disaster Response Support System based on Activities of Public-private Partnerships:
Authors: Lee Sohee
Published: March 2020

Recently, drones have been widely used in public areas such as disaster relief and rescue, information collection and monitoring of disaster affected areas. In particular, drones are highly useful as a means to quickly identify the extent of disaster damages in the broader range. However specialized skills for drone’s operation are required that means it takes effort and time to train human resources, and also need a budget to preparing equipment. Moreover it is difficult to monitor the disaster situation with government office’s own personnel and equipment if the event were happened in a wide-scale disaster. In this regard, we believe that the cooperation system with activating private drone experts in local area is meaningful way, because they already have expertise and well trained – top level of drone’s operation skills – to monitor the disaster situation in case of necessity. According to consciousness survey for civilian drone experts about the public-private cooperation, they are ready for action with a sense of duty to protect their family and neighbor’s property and human life, and also well known the geographical feature and vulnerable area. Not only do those things help to disaster management, but those make an encouraging their active participation. In this perspective, the research aims at providing a new public-private cooperation model in order to support disaster response based on the expertise and initiative of private sector. We established the operation process with public-private cooperation, in this bottom line drone emergency operation team is effectively organized and activated to support disaster response for 19th Typhoon of Soulik in August 2018. In this presentation, we would like to share our experience and efforts about activating a model of public-private cooperation.
Organic carbon storage in the biomass and soils of hedgerows
Authors: Drexler Sophie , Don Axel
Published: March 2020

The establishment of hedgerows as traditional form of agroforestry in Europe is a promising strategy to promote carbon sinks in the context of climate change mitigation. However, only few studies quantified the potential of hedgerows to sequester and store carbon. We therefore conducted a meta-analysis to gain a quantitative overview about the carbon storage in the above- and below-ground biomass and soils of hedgerows.

Soil organic carbon (SOC) data of hedgerows and adjacent agricultural fields of nine studies with 83 hedgerow sites was compiled. On average, the establishment of hedgerows on cropland increased SOC by 32%. No significant differences were found between the SOC storage of hedgerows and that of grassland. The literature survey on the biomass carbon stocks of hedgerows resulted in 23 sampled hedgerows, which were supplemented by own biomass data of 49 hedgerows from northern Germany. Biomass stocks increased with time since last coppicing and hedgerow height. The mean (± SD) above-ground biomass carbon stock of the analysed hedgerows was 48 ± 29 Mg C ha-1. Below-ground biomass values seemed mostly underestimated, as they were calculated from above-ground biomass via fixed assumed root:shoot ratios not specific for hedgerows. Only one study reported measured root biomass under hedgerows with a root:shoot ratio of 0.94:1 ± 0.084. With this shoot:root ratio an average below-ground biomass carbon stock of 45 ± 28 Mg C ha-1 was estimated, but with high uncertainty.

Thus, the establishment of hedgerows on cropland could lead to a SOC sequestration of 1.0 Mg C ha-1 year-1 over a 20-year period. Additionally, up to 9.4 Mg C ha-1 year-1 could be sequestered in the hedgerow biomass over a 10 year period. In total, hedgerows store 106 ± 41 Mg C ha-1 more C than croplands. Our results indicate that organic carbon stored in hedgerows is similar high as in forests. We discuss how the establishment of hedgerows, especially on cropland, can thus be an effective option for C sequestration in agricultural landscapes, meanwhile enhance biodiversity, and soil protection.
Resonant coupling of mode-1 and mode-2 internal waves by topography
Authors: Liu Zihua , Grimshaw Roger , Johnson Edward
Published: March 2020

We consider the resonant coupling of mode-1 and mode-2 internal waves by topography. The mode-2 wave is generated by a mode-1 internal solitary wave encountering variable topography in the framework of a pair of coupled Korteweg-de Vries (KdV) equations.  Three cases (A) weak resonant coupling, (B) moderate resonant coupling, (C) strong resonant coupling, are examined using a three-layer fluid system with fixed total depth but different  layer thicknesses, and each case has two  different topographic slopes, gentle and steep, respectively.  The criterion for the strength of the resonant coupling is  the ratio of the  linear phase speeds c2 for mode-2 and c1 for mode-1 waves.  This ratio c2/c1 varies  from 0.42-0.48 (A), 0.58-0.72 (B), to 0.44-0.92 (C). The simulations using the coupled KdV model are compared with a KdV model for the evolution of a mode-1 wave alone. In case (A) a convex mode-2 wave of small amplitude is generated by a depression incident mode-1 wave and the feedback on mode-1 wave is negligible. In case (B) a concave mode-2 wave of  comparable amplitude to the incident mode-1 wave is formed from a depression incident mode-1 wave; strong feedback enhances the polarity change process of the mode-1 wave. In (C) a concave mode-2 wave of large wave amplitude with wave fission is produced by an elevation incident mode-1 wave; strong feedback from the mode-2 wave suppresses the fission of the mode-1 wave. In all cases, the amplitudes of the generated mode-2 waves are proportional to the topographic slope.
Mapping increases in hyporheic exchange from channel-spanning logjams
Authors: Singha Kamini , Doughty Megan , McFadden Sawyer , Sawyer Audrey Hucks , Wohl Ellen
Published: March 2020

Logjams increase hydraulic resistance and create hydraulic head gradients along the streambed that drive groundwater-surface water exchange. Here, we quantify changes in hyporheic exchange flow due to channel-spanning logjams using field measurements and numerical modeling in MODFLOW and MT3DMS. Electrical resistivity (ER) imaging was used to monitor the transport of solutes into the hyporheic zone during a series of in-stream tracer tests supplemented by in-stream monitoring. We conducted experiments in a variety of reaches in Little Beaver Creek, Colorado (USA) of varying complexity: a control reach with no logjams, a reach with a single, channel-spanning logjam, and additional jams with greater logjam complexity. Our results show that 1) higher hyporheic exchange flow occurs at reach with logjams, 2) logjams create complex hyporheic exchange flow pathways that can cause bimodal solute breakthrough behavior downstream, and 3) higher discharge rates associated with spring snowmelt increase the extent and magnitude of hyporheic exchange flow. The numerical modeling supports all three field findings, and also suggest that lower flows increase solute retention in streams, although this last conclusion is not strongly supported by field results. This study represents the first use of ER to explore hyporheic exchange flow around a naturally occurring logjam over different stream discharges and has implications for understanding how logjams influence the transport of solutes, the health of stream ecosystems, and stream restoration and conservation efforts.
Moisture recycling over the Iberian Peninsula. The impact of 3DVAR data assimilation
Authors: González-Rojí Santos J. , Sáenz Jon , Díaz de Argandoña Javier , Ibarra-Berastegi Gabriel
Published: March 2020

The moisture recycling is defined as the fraction of precipitation over a delimited region that comes from the evaporation over that region. Its importance lies in the fact that it is an approximated measurement of a regional feedback between the atmosphere and the surface. Thus, this study estimates the spatio-temporal distribution of moisture recycling over the Iberian Peninsula (IP), and focuses on the impact of the use of 3DVAR data assimilation during the modeling stage.

For that purpose, two different simulations were run using the Weather and Research Forecasting (WRF) model with a horizontal resolution of 15 km over the IP. The first simulation (WRF N) was nested inside ERA-Interim as usual in numerical downscaling exercises, with information passed to the domain through the boundaries. The second run (WRF D) presents the same configuration as WRF N, but it also includes 3DVAR data assimilation step every six hours (at 00, 06, 12 and 18 UTC). Sea surface temperature was updated daily, and observations in PREPBUFR format included in the NCEP ADP Global Upper Air and Surface Weather Observations dataset were used for the data assimilation step. Only those inside a 120-minute window centered at the analysis times were assimilated. Both simulations cover the period 2010-2014, but the experiment WRF D was extended later until 2018.

The lowest values of moisture recycling (around 3 %) are obtained from November to February, while the most remarkable values are observed in spring (around 16 %) in both simulations. The moisture recycling is confined to the southeastern corner of the IP during winter. However, during spring and summer, a gradient of higher values towards the northeastern corner of the IP are observed in both simulations. The differences between simulations, associated to the dryness of the soil in the model, are highlighted during summer and autumn. WRF D presents a lower bias and produces more reliable results because of a better representation of the atmospheric moisture.

A Cross-Correlation Function (CCF) based analysis was performed for each combination of moisture recycling, accumulated precipitation and mean soil moisture over the IP. For the common period (2010-2014), the results show that the WRF D experiment extends the lifespan of moisture over the IP. The CCF analysis for soil moisture against precipitation also shows an unphysical negative lag (-1 month) for WRF N, whilst for WRF D both variables are simultaneous. For the extended WRF D simulation (2010-2018), it was found that the delay between precipitation and moisture recycling over the IP is five months.
Modelled response of marine ecosystems to Last Glacial Maximum forcing
Authors: Saini Himadri , Kvale Karin F. , Meissner Katrin J. , Menviel Laurie , Missiaen Lise
Published: March 2020

Marine plankton play a key role in climatic transitions through their ability to transfer atmospheric carbon dioxide (CO2) to the deep ocean via the biological pump. It has been suggested that the lower atmospheric CO2 concentrations during the Last Glacial Maximum (LGM) might have resulted from enhanced export production triggered by higher micronutrient (Fe, Si) availability from continental dust, particularly in the Southern Ocean. Such a scenario is consistent with higher sediment accumulation rates observed during the LGM.

In this study we use a new competition-driven ecosystem model that includes four major plankton types (diazotrophs, coccolithophores, diatoms and other general phytoplankton) to investigate their response to LGM climatic boundary conditions and to reconstructed micronutrient (Fe, Si) availability. We apply different dust fluxes, based on two plausible reconstructions (Mahowald et al., 2006 and Ohgaito et al., 2018). We compare LGM simulations with preindustrial simulations and disentangle the simulated ecosystem response due to climate forcing from the response due to micronutrient availability. We find that the ecosystem responses are complex and spatially heterogenic.
Women in UK Ocean Science: Experiences of female leadership roles at sea
Authors: Hendry Katharine ,   Women in UK Ocean Science
Published: March 2020

Women experienced significant barriers to fulfilling leadership roles in the earlier years of oceanography and marine science, in common with other scientific fields, especially those that require long expeditions away from ‘home’ and under conditions that were perceived as physically and mentally challenging. However, in recent years more women have become involved in ocean-going science, a trend that has gone hand-in-hand with adjustments in attitudes, opportunities, support during career breaks, and practical logistics on research vessels. Now, in the UK and many other countries, it has become standard to have a strong representation of women on board oceanographic expeditions, including in positions of leadership and on extended expeditions to remote locations.

Here, we have brought together a group of UK-based female oceanographers from different career stages to reflect on experiences of leadership at sea. We will share our positive stories of empowerment, evidence how diversity improves working at sea, and identify ongoing challenges that women face in marine science, and some possible solutions. Our key message is that all roles are now available to women, from chief scientist to technician, and from engineer to captain.
Mechanisms for AMOC decline in the late 20th Century
Authors: Megann Alex , Blaker Adam , Josey Simon , New Adrian , Sinha Bablu
Published: March 2020

The recent decline in the Atlantic meridional overturning circulation (AMOC) has attracted more than a little interest. The strongest AMOC recorded by the RAPID campaign at 26°N was at the start (2004/5), after which it declined about 3 Sv with a pronounced minimum in 2010. Proxies based on temperature and surface elevation have been used to extrapolate the AMOC strength before the RAPID era, and point reasonably reliably to a maximum strength in the mid 1990s, followed by a rise to a maximum at the start of the RAPID campaign in around 2005. Further back, less robust proxy data suggest that the AMOC gradually rose from the 1970s to the peak in 1990. This raises two questions: firstly, what drove these decadal variations in the overturning circulation (and hence of the ocean heat transport); and secondly whether there are observations that lead to useful predictive skill for changes in the AMOC. The surface-forced streamfunction, estimated from modelled/observed buoyancy fluxes, has been shown to be a reasonably good predictor of decadal changes in the overturning strength, preceding the latter with a lead time of about 5 years. although the reliability of the correlations before 2000 is limited by data sparsity, and especially so in the pre-satellite era.

To verify a causal link between surface forcing and decadal variations in the AMOC over longer timescales, numerical simulations present a powerful tool. A set of hindcast integrations of a global 0.25° NEMO ocean configuration has been carried out from 1958 until nearly the present day, with a selection of standard surface forcing datasets (CORE2, DFS5.2 and JRA55). These show an evolution of the AMOC strength from 1970 onwards which is consistent, both between forcing datasets and with that inferred from observations. The surface-forced streamfunction is evaluated for these experiments and is used to relate the time evolution of the AMOC to changes in the individual components of the buoyancy flux, and the surface heat loss from the Labrador and Irminger Seas is found to be the dominant predictor of AMOC changes.
Automation of the interactive mode of the homogenisation software HOMER for climatological applications
Authors: Joelsson Magnus , Slättberg Nils , Carnebring Alicia , Sturm Christophe , Engström Erik
Published: March 2020

The homogenisation software HOMER has proven to be a reliable tool for the homogenisation of temperature and precipitation observation series. The homogenisation with HOMER requires the interaction of an operator, which makes the procedure time consuming, sensitive to arbitrary choices or error by the operator, and difficult to reproduce.

HOMER uses three methods for the detection of homogeneity breaks: A pairwise comparison method (PRODIGE) for break detection on annual, seasonal or monthly basis, a two-factor model for joint-detection (ANOVA), and an ACMANT style method for the detection of homogeneity breaks in the amplitude of the seasonal cycle. The operator reviews the results of the different methods and confirms or rejects suggested breaks. HOMER can also be run in a automatic mode, where all suggested breaks from the joint-detection and the ACMANT style detection methods are confirmed and all suggested breaks from the pairwise method are rejected. Note, that also the automatic mode of HOMER requires some interactions, such that nor this mode is suitable for batch processing. 

The homogenisation with HOMER of temperature observations at SMHI has previously been performed with a set of criteria for the confirmation of a suggested homogeneity break. These criteria has been implemented in the HOMER (interactive mode) source code by assigning the break signals from the methods different weights and applying a threshold for the sum of the weighted break signals each year for the confirmation of a break year. The user can chose to adjust these threshold and weights to fit their needs. All user interactions are removed to enable batch processing.

The new automatic mode of HOMER are applied on the synthetic benchmark data set INDECIS and to Swedish observational data from 80 coupled weather stations over the time period from 1860 to 2018. For the INDECIS data set, the positions of the breaks are known and a corresponding data set without breaks are available. Current default settings and settings optimised to minimise the deviation of the homogenised data from the INDECIS clean data are used. The results are compared with results of the interactive and standard automatic mode of HOMER, and other state-of-art homogenisation tools along with known potential homogeneity breaks from meta data.
Using Bayesian Network for Soil Organic Carbon Prediction despite its Incredible Complexity
Authors: Sedighi Tabassom , Hannam Jacqueline , Corstanje Ron
Published: March 2020

In this research, static Bayesian networks (BN) is presented for predicting Soil Organic Carbon (SOC) in the complex and open soil systems. BN is a graphical computational model which provides a simple technique to define the nonlinear dependencies and, therefore, to implement a compact representation of the complex systems. Moreover, the BN is used as a simulation tool for effective processing of the complex system outcomes by probability propagation methods. This permits evaluation and potential intervention in complex soil systems and determines the dependencies between different variables. We use a BN to identify key factors in predicting England and Wales SOC. Then, we explore the relationships between different key factors such as geographical, environmental or climate and their roles individually in predicting SOC, particularly to identify those which have the highest impact. The proposed BN is also used to calculate the effectiveness of these interventions where the uncertainties associated with these casual relationships at the same time. This approach works with data from the variety of sources and handles a mix of subjective and objective data and can incorporate variables which differ across the contexts. The effectiveness of the technique is demonstrated with a case study to predict SOC.
Algorithmic Differentiation for Cloud Schemes
Authors: Baumgartner Manuel , Sagebaum Max , Gauger Nicolas R. , Spichtinger Peter , Brinkmann André
Published: March 2020

Numerical models in atmospheric sciences do not only need to approximate the flow equations on a suitable computational grid, they also need to include subgrid effects of many non-resolved physical processes. Among others, the formation and evolution of cloud particles is an example of such subgrid processes. Moreover, to date there is no universal mathematical description of a cloud, hence many cloud schemes were proposed and these schemes typically contain several uncertain parameters. In this study, we propose the use of algorithmic differentiation (AD) as a method to identify parameters within the cloud scheme, to which the output of the cloud scheme is most sensitive. We illustrate the methodology by analyzing a scheme for liquid clouds, incorporated into a parcel model framework. Since the occurrence of uncertain parameters is not limited to cloud schemes, the AD methodology may help to identify the most sensitive uncertain parameters in any subgrid scheme and therefore help limiting the application of Uncertainty Quantification to the most crucial parameters.
Human-landscape Interactions along the Danube from the Neolithic to the Present in Budapest, Hungary
Authors: Viczián István , Szilas Gábor , Tóth Farkas Márton , Sípos György , Páll Dávid Gergely , Szeberényi József
Published: March 2020

Geoarchaeological and geomorphological studies were carried out on the alluvial plain of the Danube in an urban environment in the Northwest part of Budapest. The human-landscape interactions were investigated from the Neolithic to the present times.

The environmental reconstruction was produced through inter- and multidisciplinary geomorphological, archaeological, environmental historical researches, using OSL and radiocarbon dating, malacology, stratigraphy, and sedimentological analyses of samples from archaeological excavations, GIS data processing of contemporary and historical maps, archival documents and the spatial pattern of prehistoric archaeological sites.

The Danube is Europe's second longest river with a large catchment area. Its drainage basins’ climatic and environmental changes have significant effects on our case study area’s environment and its societies. The geomorphological and hydrographical evolutions’ long-term and short-term processes as well as the landscape’s episodic events were studied by investigating the geomorphological responses to climatic, fluvial and human impacts on the environment.

The landscape evolution from a nature-dominated fluvial environment to a densely built up anthropogenic landscape of a metropolis was revealed. An active river channel used to cross the research area in the Early Holocene. Today only some moderate-sized swampy, waterlogged areas refer to the existence of this former river channel and the subsequent lake and marshy environment. Through time this relict form of the Danube’s paleochannel was occupied by streams, draining surface water, ground water and abundant karstic springs. The location of the two prehistoric settlement concentrations along the Danube can be linked with the former existence of the significant tributary streams’ confluence. Geomorphological-topographical investigations of the area’s archaeological sites revealed that one of the streams has reversed its flow direction through time. From the Roman Period onward, but especially during the Modern Times, the watercourses have been canalised and their channels have been relocated. Today hardly anything is reminiscent of the former alluvial environment in this part of the capital city.
Interannual variabilities of nutrients and phytoplankton off the Changjiang Estuary in response to changing river inputs
Authors: Ge Jianzhong , Shi Shenyang , Chen Changsheng , Bellerby Richard
Published: March 2020

Coastal ecosystems are strongly influenced by terrestrial and oceanic inputs of water, sediment and nutrients. Terrestrial nutrients in freshwater discharge are particularly important for mega-river estuaries. A remarkable increase in nutrient loads transported from the Changjiang River through the estuary to the shelf has been observed from 1999 to 2016. The Finite-Volume Community Ocean Model and the European Regional Seas Ecosystem Model were coupled to assess the interannual variability of nutrients and phytoplankton under these flux dynamics. The system exhibited a rapid ecosystem response to the changing river nutrient contribution. Singular vector decomposition (SVD) analysis demonstratedthat abundant nitrate from the river was diluted by low-nitrate water transported from the oceanic domain. In contrast, phosphate exhibited local variation, suggesting the estuarine ecosystem was phosphate-limited. The SVD results showed that there were no significant correlations between the suspended sediment and nutrients, but a significant correlation between sediment and phytoplankton. The nutrient structure of the river discharge resulted in the dominance of non-diatom species in the phytoplankton bloom from spring to autumn. The ratio of diatom and dinoflagellate populations showed a rapid feedback response to the strong oscillations in river nutrient input. High diatom primary production occurred near the sediment front, whereas dinoflagellate bloom extended significantly offshore. Both diatoms and dinoflagellates had major peaks representing spring blooms from empirical orthogonal function Mode 1 and 2, and secondary peaks from Mode 2 in the autumn, which coincided with the autumn bloom.
Crystal structures and high-temperature vibrational spectra for synthetic boron and aluminum doped hydrous coesite
Authors: Ye Yu , Miao Yunfan , Smyth Joseph R. , Zhang Junfeng
Published: March 2020

Coesite, a high-pressure SiO2 polymorph, has drawn extensive interest from the mineralogical community for a long time. In this study, we synthesized hydrous coesite samples with different B and Al concentrations at 5 and 7.5 GPa (1273 K). The B concentration could be more than 400 B/106Si with about 300 ppmw. H2O, while the Al content can be as much as 1200 ~ 1300 Al/106Si with CH2O restrained to be less than 10 ppmw. Hence, B-substitution may prefer the mechanism of Si4+ = B3+ + H+, whereas Al-substitution could be dominated by 2Si4+ = 2Al3+ + OV. The doped B3+ and Al3+ cations may be concentrated in the Si1 and Si2 tetrahedra, respectively, and make noticeable changes in the Si-O4 and Si-O5 bond lengths. In-situ high-temperature Raman and Fourier Transformation Infrared (FTIR) spectra were collected at ambient pressure. The single crystals of coesite were observed to be stable up to 1500 K. The isobaric Grüneisen parameters (ϒiP) of the external modes (< 350 cm-1) are systematically smaller in the Al-doped samples, as compared with those for the Al-free ones, while most of the OH-stretching bands shift to higher frequencies in the high temperature range up to ~ 1100 K
Hydrological causes of extreme flood events and dependence on flood type
Authors: Schumann Andreas , Fischer Svenja , Bühler Phillip
Published: March 2020

Extreme flood events can occur due to manifold combinations of different generating factors. A differentiation into flood types helps to distinguish between the main runoff generating processes and the shape of the flood wave. However, the genesis of extreme flood events cannot always be explained by the flood type only. In a first step, flood peak and flood volume are classified to determine their extremity by a robust classification based on moments. Extreme cases of runoff generating processes like the amount of event precipitation, runoff coefficient and antecedent soil moisture are detected by their deviation from the population distribution. With this, we then analyse significant coherences between the drivers of extreme runoff generating processes and the extreme flood characteristics. It turns out, that the different flood types show very different coherences between these two factors. Moreover, many extreme peaks cannot be explained by either of these factors. Instead, the spatial and temporal distribution of precipitation plays the most important role, especially for floods caused by short and medium rain. In a second step, these two factors are included in the coherence analyses, where significant dependencies of the extremity of the flood peak on these are detected. The approach is applied to several basins in Germany and Austria, including alpine, mountainous and flatland catchments. For these, significant spatial differences in the coherences occur. In the alpine catchments e.g. the soil moisture has much more impact on the extremity of floods than for flatland catchments.
Volcanic debris avalanches - from collapse to hazards
Authors: Roverato Matteo , Dufresne Anja , Procter Jon
Published: March 2020

This year marks the 40th anniversary of the 1980 Mt. St. Helens eruption and sector collapse. In acknowledgement to the vast research dedicated to understanding volcano collapse and debris avalanche dynamics, we have collated in a book the topic’s current state of the art. Within 12 chapters, this book contains reviews of and new insights from the work done over the past four decades, and provides outlooks and recommendations for future research. It is part of the Springer Book Series ‘Advances in Volcanology’ and the chapters contributed by a team of experts cover the following topics:

Introduction 

A historical perspective on lateral collapse and debris avalanches

Terminology and strategy to describe volcanic landslides and debris avalanches 

Distribution and geometric parameters of volcanic debris avalanche deposits 

Destabilizing factors that promote volcano flank collapse

Volcanic debris avalanche transport kinematics and emplacement mechanisms

Sedimentology of volcanic debris avalanche deposits

Climatic and paleo-climatic implications 

Computer simulation of volcanic debris avalanches

Volcanic debris avalanche deposits in the context of volcaniclastic ringplain successions

Cyclicity in edifice destruction and regrowth 

Volcanic island lateral collapses and submarine volcanic debris avalanche deposits

Finally, the aim of the book is to reach the professional research community as well as students and a broader audience interested in hazard management in volcanic environments.
Nonlinear autoregressive neural networks to predict fracturing fluid flow into shallow groundwater
Authors: Taherdangkoo Reza , Tatomir Alexandru , Taherdangkoo Mohammad , Sauter Martin
Published: March 2020

Hydraulic fracturing fluid migration from the deep subsurface along abandoned wells may pose contamination threats to shallow groundwater systems. This study investigates the application of a nonlinear autoregressive (NAR) neural network to predict leakage rates of fracturing fluid to a shallow aquifer in the presence of an abandoned well. The NAR network was trained using the Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms. The dataset employed in this study includes fracturing fluid leakage rates to the aquifer overlying the Posidonia shale formation in the North German Basin (Taherdangkoo et al. 2019). We evaluated the performance of developed models based on the mean squared errors (MSE) and coefficient of determination (R2). The results indicate the robustness and compatibility of NAR-LM and NAR-BR models in predicting fracturing fluid leakage to the aquifer. This study shows that NAR neural networks are useful and hold a considerable potential for assessing the potential groundwater impacts of unconventional gas development.

References

Taherdangkoo, R., Tatomir, A., Anighoro, T., & Sauter, M. (2019). Modeling fate and transport of hydraulic fracturing fluid in the presence of abandoned wells. Journal of Contaminant Hydrology, 221, 58–68. https://doi.org/10.1016/j.jconhyd.2018.12.003
Aerosol properties obtained on cloudless days through direct broadband solar radiation measurements
Authors: Zaiani Mohamed , Irbah Abdanour , Djafer Djelloul , Delanoe Julien
Published: March 2020

Anthropogenic and natural aerosols are important atmospheric constituents that can significantly reduce, by scattering and absorption, the solar radiation reaching the Earth’s surface. This impact depends on the aerosols properties, namely the optical thickness (τ), the exponent (α) and the coefficient (β) of Angström. These three parameters are first estimated by fitting the direct solar radiation measurements recorded on clear days with the Iqbal C model. The retrieval of τ and β using data collected in Tamanrasset, Southern Algeria, are in good agreement with those of retrieved by AERONET at the same time and location. However, α exponent comparison is not satisfactory, we have therefore developed an Artificial Neural Network method (ANN) to better estimate it. The ANN created was first learned from β and α obtained from AERONET. We then used β from the Iqbal C model with the ANN and obtain good estimate of α with R2 of 60% compared to the Angstrom exponent from AERONET. We will first give in this presentation an overview of the Iqbal C model, then present the data used and the processing method, and finally discuss the main results of this study.
Space Weather Effects on Proton Flux Variations in the South Atlantic Anomaly: A Numerical Study performed by Test Particle Simulations
Authors: Girgis Kirolosse , Hada Tohru , Matsukiyo Shuichi
Published: March 2020

In this study, we assess the hourly variations of the three-dimensional proton flux distribution inside the South Atlantic Anomaly (SAA) during a geomagnetic storm. We have developed a relativistic three-dimensional guiding center test particle simulation code in order to compute the proton trajectories in a time-varying magnetic field background provided by Tsyganenko model TS05 and the corresponding time-varying inductive electric field. The Dst index is the main input parameter to the simulation model, while the maximum proton flux, the area of the SAA calculated below a selected threshold, and the penetration depth of the protons are the main output variables investigated in this study were. Since the LEO spacecraft and human-related activities are already affected by space weather conditions, the South Atlantic Anomaly (SAA) is also believed to create an additional source of risk. As the radiation environment depends essentially on the particle flux, the objective of this study is to estimate quantitatively the proton flux variations inside the South Atlantic Anomaly (SAA) in quiet and in storm conditions. So far, it was found that after several drift periods, the protons in the South Atlantic Anomaly (SAA) could penetrate to lower altitudes during geomagnetic storm event, and that, the SAA maximum flux value and the corresponding area, varied differently with respect to altitudes. Numerical results were compared with observations by NOAA 17 and RD3R2 instrument mounted on International Space Station (ISS).
Hydro-geomorphological response to changes in the spatial structure of extreme rainfall in a warmer world
Authors: Peleg Nadav , Skinner Chris , Fatichi Simone , Molnar Peter
Published: March 2020

Spatial characteristics of extreme rainfall are expected to change with increasing temperatures. Extreme rainfall directly affects streamflow and sediment transport volumes and peaks, yet the effect of climate change on the small-scale spatial structure of extreme rainfall and subsequent impacts on hydrology and geomorphology remain largely unexplored. Motivated by this knowledge gap, we conducted a numerical experiment in which synthetic rainfall fields representing extreme rainfall events of two types, stratiform and convective, were simulated using a space-time rainfall generator model (AWE-GEN-2d). The rainfall fields were modified to follow different spatial rainfall scenarios, associated with increasing temperatures, and used as inputs into a landscape evolution model (CAESAR-Lisflood). We found that the response of the streamflow and sediment yields are highly sensitive to changes in total rainfall volume and to a lesser extent to changes in localized peak rainfall intensities. The morphological (erosion and sediment transport) components were found to be more sensitive to changes in rainfall spatial structure in comparison to the hydrological components, and more sensitive to convective rainfall than stratiform rainfall because of localized runoff generation and erosion production. In addition, we showed that assuming extreme rainfall events to intensify with increasing temperatures without introducing a change in the rainfall spatial structure might lead to over-estimation of future climate impacts on basin-wide hydro-geomorphology.
Extraction of electron density profiles with geostationary satellite-based GPS side lobe occultation signals
Authors: Li Wenwen , Li Min , Zhao Qile , Shi Chuang , Fang Rongxin
Published: March 2020

Electron density profiles (EDP) obtained by GNSS radio occultation (RO) technique can improve the primary ionospheric parameters. However, current studies mainly focused on GNSS RO measurements observed by low Earth orbit satellites, which can only estimate EDP at low altitudes typically below 1000 km. We investigated the GPS RO measurements recorded on the geostationary earth orbit (GEO) satellite TJS-2 (telecommunication technology test satellite II). To improve EDP derivation precision, the total electron content derived from TJS-2 single-frequency excess phase is refined by a moving average filter, which can smooth high-frequency errors and indicate higher precision over the single-difference technique. By comparison with the ground-based digisonde, the IRI 2016 model and the Constellation Observing System for Meteorology, Ionosphere, and Climate satellite (COSMIC) EDPs, the TJS-2 ionospheric EDPs show good agreement with correlation coefficients exceeding 0.8. The TJS-2 average NmF2 differences compared to digisondes and COSMIC results are 12.9% and 1.4%, respectively, while the hmF2 differences are 1.65 km and 1.76 km, respectively. With a GEO satellite such as TJS-2, the side lobe GPS RO signals can also be received, and they are employed to estimate electron densities up to several thousand kilometers in height for the first time in this contribution. Our results also reveal that GEO-based RO signals can estimate EDPs at specific locations with daily repeatability, which makes it a very suitable technique for routinely monitoring EDP variations