bluuebunny/crossref_metadata_2025 huggingface dataset:
Geometry of LGM polygonal sorted patterns analysed using high-resolution airborne data (Krkonoše Mountains, Czech Republic)
Authors: Uxa Tomáš , Křížek Marek , Krause David , Dlabáčková Tereza
Published: March 2022

Relict sorted patterns are valuable indicators of past permafrost and climate evolution, but their detailed terrain explorations are usually challenging due to high time requirements and poor pattern visibility. Here, we test the applicability of high-resolution airborne data to map and analyse the geometry of LGM polygonal sorted patterns at one site in the Krkonoše Mts., Czech Republic. We delineated a total of 2000 sorted patterns using colour contrasts between their elevated centres and bordering troughs discernible on a LiDAR digital elevation model with a resolution of 0.5 m and on true-colour orthogonal aerial photographs with a resolution of 0.2 m. Since the patterns occupy an area of ~1.96 ha, the density of their network accounts for ~1019 cells per hectare. The patterns have a diameter of 3.59±0.95 m, a height of 0.30±0.11 m, and an estimated sorting depth of 1.00±0.26 m. The number of pattern sides ranges between three and ten, but 82 % of the patterns are pentagonal to heptagonal, and their sides mostly meet at three- or four-way intersections at an angle of 120±24°. However, isometric patterns are rather rare as a length-to-width ratio attains 1.48±0.30. Generally, the remotely-sensed pattern attributes are consistent with ground-truth data previously collected at the study site, which proves the utility of high-resolution airborne data to rapidly map and complexly analyse the geometry of large sets of relict landforms over extensive areas that could not be done by conventional terrain surveys. The sorting depth indicates that permafrost superimposed by ~1 m thick active layer occurred at the study site during the LGM, which can be further used for past permafrost and climate modelling. The dataset can also have many other applications such as for validating automated pattern mapping/delineation tools and pattern growth models or for choosing an effective sample size for future surveys.

The research is financially supported by the Czech Science Foundation, project number 21-23196S.
Reconstructing five decades of suspended sediment yields at two high alpine gauges in the Ötztal, Austria, using quantile regression forests
Authors: Schmidt Lena Katharina , Francke Till , Grosse Peter , Mayer Christoph , Bronstert Axel
Published: March 2022

Suspended sediment export from partly glaciated high alpine catchments is not only relevant for ecosystems, but also for infrastructure and flood hazard alterations in downstream areas. In order to estimate future changes, it is important to assess long-term developments in past sediment yields. However, existing records of suspended sediment export are mostly too short to investigate these long-term changes. For example, for the two gauges “Vent Rofenache” and “Vernagtferner” in the high alpine and partly glaciated Upper Ötztal in Tyrol, Austria, only 15 and four years of turbidity measurements exist, respectively, precluding robust explorations of longer-term developments.

To compensate for this lack of measurement data, we use a Quantile Regression Forest approach, a non-parametrical, multivariate tool based on regression trees. It allows for reconstructing continuous sedigraphs based on short-term or point-like sediment concentration data and continuous predictor variables such as discharge (Q), precipitation (P) and air temperature (T).

At gauge “Vernagtferner”, turbidity-based sediment concentration data were available only for the years 2000, 2001, 2019 and 2020. To test the ability of our model to reconstruct past sediment concentrations, we trained our model using the 2019 and 2020 data and validated against the 2000 and 2001 measurements, which showed good agreement (Nash-Sutcliffe Efficiency of 0.73). At gauge “Vent Rofenache”, the hydrographic service of Tyrol, Austria, has recorded turbidity-based sediment concentration data since 2006. Our model showed to be well able to reconstruct sediment yields based on by these data (out-of-bag Nash-Sutcliffe efficiency of 0.66).

This validation enabled us to confidently use the long-term availability of the predictor variables (Q, P, T) to reconstruct sediment yields at gauge “Vernagtferner” since 1974 and at gauge “Vent Rofenache” since 1967.

The resulting dataset allows us to

Analyze annual sediment yields with respect to trends and change points for time series of 47 and 54 years, respectively,

Examine changes in the predictor variables,

and connect developments in sediment yields to mass balances of the large glaciers within the catchment.

Current results point at an almost step-like increase in annual sediment yields at the beginning of the 1980s at both gauges. This coincides with a marked increase in discharge volumes that in turn correlate with a basic change in glacier mass balances.
Moho depths beneath the European Alps from receiver functions of the AlpArray Seismic Network
Authors: Michailos Konstantinos , Scarponi Matteo , Stipčević Josip , Hetényi György , Hannemann Katrin , Kalmár Dániel , Mroczek Stefan , Paul Anne , Plomerová  Jaroslava , Tilmann Frederik , Vergne Jerôme , AlpArray Working Group the AlpArray Receiver Function Research Group
Published: March 2022

The European Alps, formed by the interactions between the European and Adriatic plates, is a unique geological structure that has been extensively studied over the past decades. Despite numerous active and passive seismic investigations in the past, the crustal structure across the whole Alpine domain is somehow limited - mainly due to the limited number of seismometers available. The deployment of the AlpArray Seismic Network provides, which consisted of around 600 broadband seismometers and was operational from early 2016 till mid-2019, offers a unique opportunity to further update the current knowledge of the crustal structure beneath the European Alps by employing Receiver function (RF) analysis. 

RF method can provide an efficient way to image the structures and the discontinuities within the uppermost part of the Earth. We use teleseismic earthquakes with M≥5.5 and M<8.5 and epicentral distances ranging between 30 and 90 degrees that occurred during the operational time of the AlpArray Seismic Network. We compute RFs using a time-domain iterative deconvolution method. We apply quality control steps to both the original three-component waveforms and the calculated RFs to ensure that we only use high-quality signals. 

As of abstract submission, we are in the process of calculating the RFs. We also intend to perform a time to depth migration, in a 3D spherical coordinate system, to the RFs. This methodology, together with unprecedented data coverage, will provide us with migrated profiles that will image the structure of the crust and map the Moho depths at a great level of detail. 
Variation of soil microaggregate stability as a function of WRB reference soil groups and diagnostic properties
Authors: Labancz Viktória , Barna Gyöngyi , Szegi Tamás , Bieganowski Andrzej , Bakacsi Zsófia , Novák Tibor , Makó András
Published: March 2022

Microaggregates are structural elements of the soil smaller than 250 µm. These microaggregates are composed from diverse mineral, organic and biotic materials that are bound together during the process of pedogenesis (through a variety of ways and processes). According to the general theories, microaggregates are predominantly stabilized by organo-mineral complexes, which are relatively stable and are not easily degraded by changes in soil organic matter content as a result of land use and cultivation. At present, the relationship between soil processes and the formation of microaggregate stability needed further studies to gain a better understanding

In our study, we were looking for a quantifiable relationship between the stability of microaggregates and different soil reference groups and diagnostic properties. We examined 55 Hungarian soil profiles, which were selected on the basis of their various parameters. The stability of the microaggregate was determined by laser diffractometry (LDM) with a Malvern Mastersizer 3000, Hydro LV dispersion unit, as the ratio of dispersed to non-dispersed clay content. The measured data were sorted into a database and a statistical analysis were performed between the soils and WRB diagnostic properties of each reference group and the stability of the microaggregate. Based on our results, different significant soil groups could be identified, furthermore there is a good connection between the stability of the microaggregate and the soil reference groups. There is also a clear difference between the horizons of cultivated and uncultivated soils.

This research is supported through the common grant of the Hungarian and Polish Academy of Sciences (Grant No. NKM-2019-17) and by the Hungarian National Research, Development and Innovation Office Foundation (Grant No. OTKA K 119475).
Earthen Building materials to mitigate Urban Heat: An Urban Microclimate and Human Thermal Comfort Study across various neighborhood types
Authors: Ibitolu Henry , Zhao Qunshan , Beckett Chris , Fosas Daniel
Published: March 2022

In times of rapid global urbanization, the ability to accurately predict the expansion and impact of urban densification on the local climate is critical to the health and wellbeing of the society. Urban densification is the phenomenon of increasing the number or size of urban structures without increasing urban footprint. The characteristics of urban areas such as- the types of building materials, the geometry or orientation, and the land use zoning including amount of green spaces, all contributes to the urban thermal composition, and intensity of urban warming. However, densification reduces the amount of shade and green or free space per structure, whilst also increasing the paved surface area, thus creating a “heat island (UHI)” due to the mutual heating of building structures and the surrounding infrastructures. In this study, we examine the potential of mitigating the heat island effects through leveraging on thermally massive, low-embodied carbon earth building materials. Such materials have been shown to absorb excess heat, and so may buffer heat island effects whilst simultaneously reducing overall air conditioning energy demands. The effect of adopting these earth materials is examined at the neighborhood scale using state of the earth ENVI-met CFD simulation for urban microclimate and outdoor human thermal comfort modelling. Thus, to understand the consequent impact on neighborhood level changes in urban heat after changing housing materials, the study analyzed different residential neighborhood types (compact, open and sparse low-rise) using the Local Climate Zones (LCZ) classification. Also, various types of earth-based wall construction methods were modelled to evaluate the corresponding impact on the immediate outdoor atmospheric and human thermal comfort conditions. In this contribution, we investigate the hypothetical scenario of replacing conventional cement building materials with traditional earth based alternatives in mitigating emerging UHI effects and show results across different residential neighborhoods.  Ultimately, our findings will help modify construction practices in urbanizing areas to counter urban heat island phenomena effectively.
Russia’s New Forests. Controversies around the Future of Abandoned Farmland
Authors: Vorbrugg Alexander
Published: March 2022

Trees have regrown on dozens of million hectares of abandoned farmland in Russia over the past decades. So far, their status has remained largely informal, but recent propositions to formalize forests and forestry on abandoned farmland spurred legislatorial processes and political controversies. Besides a large-scale but unplanned and unstable forest transition over the past decades, there are now propositions to actively develop “new forests” on abandoned farmland.

After introducing characteristics and implications of the ‘informal’ forest transition to date, I discuss how “new forests” have become a new object of political controversy but also future possibility. I show how certain “new forest” models go along with a reframing of abandoned farmland, long associated with loss and degradation, into a future-oriented vision with ecological, social, and economic benefits. The reduction of pressure on primary forests is one such potential benefit, opening up possibilities for new forestry models another one. I also discuss some of the (potentially) problematic implications of these models, such as the bracketing of local knowledge and needs, or companies’ rising interest in reforestation as a means to ‘greenwash’ emission-intensive businesses by carbon offsetting. In methodical terms, I discuss how studying new forests as a socio-natural entitiy in the making offers opportunities for original interdisciplinary collaboration.
Sensitivity of WRF microphysics schemes to Convective Permitting Simulation of January 2017 Heavy Rainfall Events in Southern Thailand
Authors: Wang Yi , Alamirew Netsanet , Dudhia Jimy , Liu Changhai , Moses Cherith , Nakhapakorn Kanchana
Published: March 2022

Heavy rainfall events are devastating, could trigger flash urban and rural river floods in some environmental settings. If we can better predict those floods, we will better protect the communities and vulnerable people. Here, we present some high-resolution regional climate model simulations to reproduce the January 2017 heavy rainfall events that occurred in Southern Thailand, causing major flash and river floods with high death tolls and significant socioeconomic impacts in the region of Krabi and Nakhon Si Thammarat provinces.  High rainfall events persisted in the region starting from January 4, 2017, peaking around January 6, and lasted until January 10. To reproduce the detailed timeline and spatial changes of heavy rainfall events, we have run the community Weather Research Forecasting (WRF) model with different combinations of cloud microphysical schemes.  The initial and lateral boundary conditions for our WRF simulations are based on the ERA5 reanalysis. The model simulations cover the period from 1st to 18th January 2017 using two nested domains with horizontal resolutions at 3-km and 9-km for the inner and outer domains, respectively. Four simulations were conducted with different cloud microphysics (WSM-6 scheme, Goddard scheme, Thompson scheme, and Purdue-Lin scheme) while keeping all other model configurations the same. In addition to these four experiments, we have also carried out one further experiment with a single domain at 3-km horizontal resolution. WRF simulations are compared using two satellite-derived measurements: 1) NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) and 2) Climate Data Prediction Morphing (CMORPH). 

 

Our WRF simulations have reproduced the spatial distribution of this particular rainfall event, but the rainfall magnitude (intensity) is underestimated as compared with observations. Furthermore, different microphysical schemes have resulted in varying magnitudes of rainfall intensities with WSM-6 and Purdue-Lin schemes performing much better as compared with both Goddard and Thompson schemes. We also found the 3-km single domain run including spectral nudging has the best result of rainfall magnitude and spatial distribution as compared with the four nested runs. This paper re-emphasizes that with some careful selection of model configurations, WRF can reproduce detailed regional atmospheric processes. The best WRF model configuration can then be used in our dynamical downscaling of the IPCC AR5 CESM model run under the RCP6.0 from 2080 to 2100.
Disaster Risk Financing systems for fluvial flood risk in Democratic Republic of Congo and Pakistan
Authors: Bevington John , Forbes Heather , Shelton Kay , Smith Richard , Wood Elizabeth , Maisey Paul , Ludlam Sophie
Published: March 2022

Flood Foresight is JBA’s strategic flood forecasting system, providing flood inundation and depth estimates at 30m resolution up to 10-days ahead of fluvial flood events.  The system is globally scalable and recent projects have seen the Forecasting module provide forecast flood footprints in Democratic Republic of Congo, Myanmar and the Indus River basin in Pakistan.  Data produced by these systems are being used for a variety of purposes including informing humanitarian anticipatory actions, parametric insurance and disaster risk financing.  This presentation will explore the use of Flood Foresight in Democratic Republic of Congo and Pakistan for the purposes of humanitarian disaster risk financing and demonstrate the benefits to this user community in otherwise data sparse regions. 

Disaster Risk Financing (DRF) programmes are being developed for the Democratic Republic of Congo and Pakistan and are designed to allow civil society actors in country to proactively manage disaster risks. By quantifying risks in advance of disasters, pre-positioning funds, and releasing them according to pre-agreed plans, the user community are better placed to enable early disaster relief actions to help reduce the human and economic costs of disasters.  In both Democratic Republic of Congo and Pakistan, JBA were tasked with developing an operational fluvial flood forecasting model which can, at lead times of 0 – 10 days ahead, predict the number of people who will be inundated by fluvial flooding.

For forecasting population impacts, JBA’s Flood Foresight system couples the Copernicus Global Flood Awareness System (GloFAS) with the Flood Foresight technology to generate daily probabilistic forecasts of flood inundation extents and depths.  From the maps generated, the system then generates estimates of the population at risk.  This fully automated early warning system is providing humanitarian organisations with daily forecasts of flood conditions to inform rapid financing for anticipatory actions designed to reduce overall humanitarian impact.  To help inform the definition of risk and subsequently set appropriate financing triggers, a probabilistic flood risk assessment was also developed using JBA’s Global Flood Model, providing national, province and territory level risk profiles of population affected by fluvial flooding.
Past and future climate trends focused on synoptic patterns in the northeast of the Iberian Peninsula
Authors: Ventura Sergi , Villalba Gara , Miró Josep Ramon , Peña Juan Carlos
Published: March 2022

Based on a centenary meteorological observatory, the mean temperature and frequency of heat waves at the city of Barcelona is increasing due to global warming. The number of heat wave episodes by climatic periods of 30 years, with a specific percentile 95 (P95) of summer maximum temperature, has been increased from 23 (1951-1980) with a P95 of 31˚C to 59 days (1991-2020) with a P95 of 32.8˚C.  Therefore, it is necessary to analyse weather circulation to understand the reason and predict the possible future impacts. In this study, heat wave events for 1951-2020 have been analysed with ERA5 data, in order to classify the different synoptic patterns and each evolution. It is possible to get climate trends from past reanalysis data, but it is also interesting to predict future possibilities. Most of the previous research is focused on temperature and precipitation while the target of this study is the mesoscale and synoptic circulation. For this reason, Coordinated Regional Climate Downscaling Experiment (CORDEX) data at 0.11˚ grid mesh has been used to analyse the future scenarios compared to the historical simulations of the same source. More specifically, for this study, it was necessary to download mean sea level pressure (MSLP) and 500hPa geopotential height (GHP) data. Due to the big amount of information, it has been applied a statistical method called Principal Component Analysis (PCA) to simplify and reduce the dimensions of the sample. Afterwards, working on a cluster analysis has been necessary to classify the simplified data. The synoptic patterns remain relatively constant throughout the last climatic periods according to ERA5, being the synoptic type “Shallow Cyclone or Undetermined pressure gradient” the recurrent type to cause heat wave periods in summer. CORDEX data shows more dynamism in comparison to ERA5 reanalysis and expects to remain similar until 2100. Northwest and north advections are expected to increase by 7.3% and 6.6% respectively and lows or cyclones are expected to decrease by 8.3% according to RCP4.5 scenarios.
The role of livestock in nitrogen pollution of large river basins: A machine learning-based assessment
Authors: Sheikholeslami Razi , Hall Jim
Published: March 2022

Livestock are known to be one of the leading sources of nitrogen and other organic pollutant contents in surface waters. In response to growing demand for animal-source foods, livestock production has shifted into more high-input systems, accompanied by increased fertilizer and animal manure application rates to produce feed, which has resulted in large losses of nitrogen. The effects of nitrogen contamination of water bodies on human and ecosystem health are not limited and localized but have large-scale implications and are rapidly becoming widespread. However, current approaches to estimate the changes in stream water quality often fail to explicitly account for livestock activities across large spatial scales. To overcome this challenge, we adopted a data-driven approach and developed a spatio-temporal water quality model. Our model is based on a popular supervised machine learning technique, known as random forests, that can efficiently handle large, heterogeneous geo-environmental datasets. The model was trained using several site-level measurements and a large set of gridded environmental covariates to predict monthly nitrogen concentrations across the world. We then performed variable importance analysis on the proposed model to identify influential drivers of nitrogen variability at global scale. Our results confirmed the prominent role of livestock population and nitrogen fertilizer use in pollution of the river systems. Finally, we quantified how much livestock has contributed to nitrogen pollution in 115 major river basins of the world. We found that during 1992-2010 the average increase in nitrogen concentrations due to livestock was about 15% globally. Importantly, model results also indicate that at some large basins livestock population is responsible for more than 50% of raise in the levels of nitrogen. These regions point to the global livestock ‘‘hot spots’’ where high nitrogen loading to waterways may be expected. The results and insights gained in this study can have important implications for better management of livestock faming systems and pollution control policies.
Broadband seismic instrumentation for monitoring CCS sites
Authors: Reis Will , Cilia Marcella , Watkiss Neil , Mohr Sally , Barbara Rui , Hill Phil
Published: March 2022

Carbon Capture and Storage (CCS) sites require microseismic monitoring before, during and after operations to ensure safety of operational personnel and the wider public.

The high dynamic range and low self-noise of broadband seismometers allows for the detection of low magnitude microseismic events which fall below the threshold of less sensitive geophones. Higher long-period sensitivity also allows the full source spectra of earthquakes to be accurately measured, resulting in more accurate magnitude estimations which improve the integrity of any microseismic monitoring system.

Borehole instruments such as the Güralp Radian are a natural fit for detecting low magnitude microseismic events. Optional high gain at the higher frequencies makes the Radian extremely suitable for monitoring low-magnitude induced events while retaining long-period sensitivity for larger ruptures. The slim form factor and omni-angle operation allows the instrument to easily be lowered into decommissioned wells with little information about the orientation at depth.

The Radian is currently being utilised by the British Geological Survey as part of the UK GeoEnergy Test Bed (GTB) to monitor and improve understanding of fluid flow through natural subsurface pathways. A string of 6 interconnected Radians provides vertical profiling around the injection site with a maximum of 8 units able to join in a single string. The Radian will detect and monitor small changes in the subsurface at the GTB as part of the suite of monitoring technologies deployed onsite. 

In addition to onshore networks, offshore depleted gas fields are becoming increasingly scrutinised for potential to store CO2. The advent of Güralp omnidirectional sensor technology combined with acoustic near-real-time data transmission means the Aquarius OBS provides a cost-effective solution for monitoring offshore CCS sites, with infrequent and rapid battery recharging and acoustic data extraction while the unit is still on the seafloor.
Spatial Ground-Level Particulate Matter (PM10) in Indonesia using Machine Learning
Authors: Permana Donaldi S , Fajariana Yuaning , Aprilina Kharisma , Nuryanto Danang E , Linarka Utoyo A , Panjaitan Andersen , Riama Nelly F , Sopaheluwakan Ardhasena , Munggaran M Rizky , Karnawati Dwikorita
Published: March 2022

Large-scale forest fires often occur in Indonesia and affect air quality and human health. The effect of forest fire on air quality quantified by rising PM10 concentration on Indonesia Meteorological, Climatological and Geophysical Agency (BMKG) observation network. A few PM10 observation networks and uneven distribution in Indonesia make it difficult to present spatial ground-level PM10.  The aim of this study was to estimate ground-level PM10 in Indonesia and present the spatial distribution of ground-level PM10 using machine learning. Support Vector Regression (SVR) techniques were used to estimate the PM10 content from heterogeneous data sources, including ground measurements provided by BMKG, numerical model data, and hotspot retrieved from NASA/LANCE – FIRMS for satellite imagery. RMSE and MSE were used to evaluate the estimation result. We also present the modeling framework on the forecast of the CAMS Copernicus model in Indonesia. The performance of various input parameter configurations of SVR for estimating the ground-level PM10 as indicated by low prediction errors.
Deep learning in spaceborne GNSS-R: Recent methodologies and atmospheric products
Authors: Xiao Tianqi , Asgarimehr Milad , Arnold Caroline , Zhao Daixin , Weigel Tobias , Mou Lichao , Wickert Jens
Published: March 2022

 

The capability of Deep Learning (DL) for operational wind speed retrieval from the measured Delay-Doppler Maps (DDMs) is recently characterized. It is shown that such techniques can lead to a significant improvement in the derived atmospheric data products. A global ocean dataset is developed processing the measurements of NASA Cyclone GNSS (CYGNSS). The model is based on convolutional layers for direct feature extraction from bistatic radar cross-section (BRCS) DDMs and fully connected layers for processing ancillary technical and higher-level input parameters. This model leads to an RMSE of 1.36 m/s and a significant improvement of 28% in comparison to the officially operational retrieval algorithm.

From the theoretical knowledge, several error sources are known, the modeling and correction of which is not easy due to their highly nonlinear interaction with other and the dependent parameters. DL is potentially able to learn such trends and correct the associated biases. For instance, rain splash on the ocean surface and swell waves alter the surface roughness, and consequently, the GNSS scattering patterns, which appear as a considerable bias in GNSS-R wind products. The magnitude of such biases is nonlinearly dependent on several technical and environmental parameters including the reflection geometry, and ocean surface state. After a brief introduction to the known physical mechanisms, we discuss how a DL-based fusion with data on bias-causing parameters, can improve the wind speed predictions.
How do Source to Sink Systems influence patterns of human settlement in the Indo-Gangetic Basin?
Authors: Aggarwal Ekta , Gupta Sanjeev , Whittaker Alexander C.
Published: March 2022

The source-to-sink (S2S) river systems in the Indo-Gangetic Basin (IGB) construct alluvial landscapes which have hosted some of the earliest human civilizations. These landscapes provide the vital sustaining resources  acting as a lifeline for settlement and agriculture. The factors contributing to its richness are climate, political security, and the alluvial landscapes formed by Indus, Ganga, and Yamuna rivers. Given the significant changes that have happened due to human exploitation of landscape, an understanding of the impact of geomorphic landscapes on human settlement patterns is lacking, hence it is important to understand changes in these source to sink landscapes over a range of spatial and temporal scales. For instance, given the risk to people on river floodplains due to natural processes such as flooding, it is important to understand the impact of geomorphic landscapes on human populations.

Here, we aim to investigate the impact of  the source to sink system on the human settlement patterns in the Indo Gangetic Plains at decadal and centennial historic timescales. Historical maps along with LANDSAT images are used for detailed mapping of the S2S landscape elements and study the long term changes in the river morphology. Previous studies mainly exploited the optical data like LANDSAT and MODIS data to map the urban areas. To investigate changes at short timescales, we use DMSP-OLS stable nightlights data to study changes in urban settlement patterns in the Gangetic basin from 1992-2013. Earlier research have demonstrated usefulness of nightlights data for urban settings for the assessment of the economic, demographic and environmental purposes. We are integrating these data sets with mapping of geomorphic elements in the Gangetic basin as well as the river network extracted from the SRTM-DEM. We use these data sets to evaluate the links between the nightlights and geomorphic features thus highlighting possible connections between population growth and geomorphic elements in the IGB.

The overall aim of this study is to provide new quantitative insights between the dynamics of human habitation and river morphodynamics in the Indo-Gangetic basin over a range of scales.
Changes of ammonia and nitrogen oxide emissions in South-eastern Europe inferred from an Elbrus (Caucasus, Russia) ice core record (1774-2009 CE)
Authors: Legrand Michel , Vorobyev Mstislav , Bokuchava Daria , Khairedinova Aleksandra , Kutuzov Stanislav , Mikhalenko Vladimir , Vinogradova Maria , Plach Andreas , Stohl Andreas , Ginot Patrick , Eckhardt Sabine , Preunkert Susanne
Published: March 2022

With the aim to reconstruct the history of atmospheric nitrogen pollution in south-eastern Europe, the ice core records of ammonium and nitrate covering the years 1774-2009 were extracted from a 182 m long ice core drilled in 2009 at Mount Elbrus in the Caucasus, Russia.

The Elbrus ammonium ice-core record indicates a 4-fold increase from pre 1780 to 1990-2010. In summer, when both the vertical atmospheric mixing and anthropogenic ammonia emissions dominated by agriculture sector are strengthened, a moderate an increase of ammonium already took place from 1774 and 1880. The summer ammonium increase accelerated a first time at the beginning of the 20th century, and a second time after 1950, levels reaching a plateau between 1980 and 2010. This ice-core trend is compared to estimated past anthropogenic NH3 emissions in Europe by using state-of-the-art atmospheric transport (FLEXPART model driven with 0.5°x0.5° ERA-5 reanalysis data) simulations of submicron aerosol. It is shown that the ammonium Elbrus ice core trend is in excellent agreement with estimates of past NH3 emissions from south-eastern Europe (South european Russia, Turkey, southern Ukraine). The ammonium level of ice deposited prior to agricultural activities is found to represent ~11-15% of the 1980-2010 level. This value is in the lower range of estimates at the global scale of the contribution of natural ammonia emission to total (natural plus anthropic) ammonia emissions.

A potentially existing trend of nitrate in the Elbrus ice core remained insignificant prior to ~1945. The well-marked 3-fold increase seen in the Elbrus ice core between 1950 and 1980 followed by a stabilization of levels between 1980 and 2010 is consistent with estimated past emissions of NOx from south-eastern Europe. In agreement with the partitioning at the global scale of natural and anthropogenic emissions of NOx, nitrate levels in Elbrus ice deposited prior to 1940 represent 26% of those deposited at the end of the 20th century.

Study supported by the Megagrant project (agreement № 075-15-2021-599, 8.06.2021)
Offshore atmospheric stability estimation from floating lidar wind profiles
Authors: Araujo da Silva Marcos Paulo , Rocadenbosch Francesc , Farré-Guarné Joan , Salcedo-Bosch Andreu , González-Marco Daniel , Peña Alfredo
Published: March 2022

In this work, we revisit the 2D parametric-solver algorithm [1] to estimate the Obukhov length, and hence, determine atmospheric stability from floating Doppler wind lidar (FDWL) wind profiles. The algorithm fits the wind-profile model derived from Monin-Obukhov similarity theory to the FDWL-measured wind profile by means of a constrained non-linear least squares optimisation. Observational data were gathered at the IJmuiden test site in the North Sea (52.848 N, 3.436 E) between March and June of 2015. The reference Obukhov length was obtained via bulk Richardson number, which was estimated from IJmuiden-mast observations. Comparisons with the reference stability are performed by using a simplified atmospheric stability classification consisting of only three types, namely stable, neutral and unstable. Fairly similar results were obtained from the 2D-estimated and the mast-derived reference stability classifications for the stability behaviour during the time of day as well as for horizontal-wind-speed dependence on the stability type.

This research is part of the projects PGC2018-094132-B-I00 and MDM-2016-0600 (“CommSensLab” Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033/ FEDER “Una manera de hacer Europa”. The work of M.P Araujo da Silva was supported under Grant PRE2018-086054 funded by MCIN/AEI/ 10.13039/501100011033 and FSE “El FSE invierte en tu futuro. The work of A. Salcedo-Bosch was supported under grant 2020 FISDU 00455 funded by Generalitat de Catalunya—AGAUR. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA-871115) and H2020 ATMO-ACCESS (GA-101008004).

[1] M. P. Araujo da Silva, F. Rocadenbosch, J. Farré-Guarné, A. Salcedo-Bosch, D. González-Marco, and A. Peña, “Assessing obukhov length and friction velocity from floating lidar observations: A data screening and sensitivity computation approach,” Remote Sensing, 2022, submitted.
Northern Sahara speleothems record timing of rainfall and moisture source during Green Sahara periods
Authors: Couper Hamish , Day Christopher , Maouche Said , Deramchi Aboubakr , Carolin Stacy , Mason Andrew , Derder Mohamed El Messaoud , Yelles Chaouche Abdelkarim , Henderson Gideon
Published: March 2022

The hyper-arid Saharan desert belt stretching across North Africa is an important part of the global climate system, with dust export shown to influence climate systems such as ENSO and distant monsoon systems. Understanding climate dynamics and potential future changes in this region is however difficult due to a paucity in both instrumental and high-resolution paleoclimate data. There is strong evidence for periods of increased rainfall across large parts of North Africa during the late Quaternary, termed ‘Green Sahara’ periods, which contribute to regional aquifer recharge and improved human population connectivity across the Sahara. There is, however, currently limited evidence regarding: i) precisely where and when rainfall occurred and; ii) the sources of moisture contributing to increased rainfall at the northern-most reaches of the Sahara.

In this study, we present new proxy reconstructions from the northern limits of the presently hyper-arid Sahara Desert, to identify moisture sources, timing and latitudinal extent of rainfall change during these so-called Green Sahara periods. We do this using several ancient fossil stalagmites collected from cave sites in the desert foothills of the central Saharan Atlas Mountains, Algeria. High-precision U-Th chronology and stable-isotope measurements on calcite samples from multiple cave sites contribute towards an east-west transect of records. Due to the locations of the caves, stalagmite growth periods and stable isotope records provide direct evidence of where and when there was significantly increased rainfall in this region, and help us to identify potential sources of moisture through time. We present these results, and their implications for a more detailed reconstruction of the occurrence of Green Sahara periods in northwest Africa.
Mercury released from newly formed volcano influence concentrations in the surrounding ocean 
Authors: Garcia Arevalo Isabel , Knoery Joël , Thomas Bastien , Torres Rodriguez Natalia , Heimbürger Boavida Lars-Eric , Cathalot Cecile , Rinnert Emmanuel ,   Geoflamme shipboard scientific party
Published: March 2022

Volcanic and geothermal areas are important natural sources of mercury, with mercury concentrations in volcanic gases above the atmospheric background. Individual volcanoes exhibit variable degassing features and behavior, leading to considerable uncertainty in global geogenic mercury fluxes estimations. Likewise, studies on mercury emissions from submarine volcanic and hydrothermal sites are scarce. Nevertheless, information on those natural inputs is needed to better estimate the anthropogenic mercury enrichment, and thus for the implementation of the Minamata convention.

During Spring 2021, the GEOFLAMME campaign took place at the northern end of the Mozambique channel, where we examined the influence of volcanic inputs from a volcano that had formed less than 2 years ago near Mayotte Island.  Water samples were obtained with a trace metal-clean CTD rosette and all-titanium high-pressure samplers using the remotely operated vehicle Victor 6000 on board R/V Pourquoi pas?. Total mercury was measured on board via Cold Vapour Atomic Fluorescence Spectroscopy (CV-AFS) following the EPA method 1631. Exhaled fluid samples from titanium samplers followed the same analytical scheme, but at the shore laboratory.

Mercury levels measured from water column showed increased concentrations near the seafloor.  Total mercury measured in fluid samples from the different venting sites showed concentrations 3 to 60 times higher than surrounding seawater.

Our study provides new insight to the understanding for mercury biogeochemistry, the interactions between magmatism, tectonics and fluids circulation processes, as well as the implications on the physical-chemical properties of the water column. It also improves our knowledge on present-day mercury cycling in the marine environment usingfield-based data. Ongoing work will attempt to quantify seafloor mercury inputs to the vicinity of the Mayotte Island.
Experimental Investigation into the long-term spatial and temporal development of Triadic Resonance Instability in a finite-width internal wave beam 
Authors: Grayson Katherine , Dalziel Stuart , Lawrie Andrew
Published: March 2022

With an aim of understanding the role of internal waves to oceanic mixing, various mechanisms have been cited as a possible explanation for how they transfer energy across the wavenumber and frequency spectra and eventually contribute to small-scale turbulence. Triadic Resonance Instability (TRI) has become increasingly recognised as potentially one of these mechanisms. This talk will summarise experimental work that examines the long-term temporal and spatial evolution of this instability in the more realistic scenario of a finite-width internal wave beam. Experiments have been conducted using a new generation of wave maker, featuring a flexible horizontal boundary driven by an array of independently controlled actuators. We present experimental results exploring the role the finite-width of a wave beam has on the evolution of TRI. Experimentally, we find that the approach to a saturated equilibrium state for the three triadic waves is not monotonic, rather their amplitudes continue to oscillate without reaching a steady equilibrium. A detailed study into the structure of the secondary waves shows that this behaviour is also witnessed in Fourier space. We show how a spectrum of these resonant frequencies in the flow ‘beat’ to cause interference patterns which manifest throughout the instability as slow amplitude modulations.
Data Access Made Easy: flexible, on the fly data standardization and processing
Authors: Bavay Mathias , Fierz Charles , Nitu Rodica
Published: March 2022

Automatic Weather Stations (AWS) deployed in the context of research projects provide very valuable data thanks to the flexibility they offer in term of measured meteorological parameters, choice of sensors and quick deployment and redeployment. However this flexibility is a challenge in terms of metadata and data management. Traditional approaches based on networks of standard stations can not accommodate these needs and often no tools are available to manage these research AWS, leading to wasted data periods because of difficult data reuse, low reactivity in identifying potential measurement problems, and lack of metadata to document what happened.

The Data Access Made Easy (DAME) effort is our answer to these challenges. At its core, it relies on the mature and flexible open source MeteoIO meteorological pre-processing library. It was originally developed as a flexible data processing engine for the needs of numerical models consuming meteorological data and further developed as a data standardization engine for the Global Cryosphere Watch (GCW) of the World Meteorological Organization (WMO). For each AWS, a single configuration file describes how to read and parse the data, defines a mapping between the available fields and a set of standardized names and provides relevant Attribute Conventions Dataset Discovery (ACDD) metadata fields, if necessary on a per input file basis. Low level data editing is also available, such as excluding a given sensor, swapping sensors or merging data from another AWS, for any given time period. Moreover an arbitrary number of filters can be applied on each meteorological parameter, restricted to specific time periods if required. This allows to describe the whole history of an AWS within a single configuration file and to deliver a single, consistent, standardized output file possibly spanning many years, many input data files and many changes both in format and available sensors. Finally, all configuration files are kept in a git repository in order to document their history.

A basic email-based interface has been developed that allows to create new configuration files, modify an existing configuration file or request data on-demand for any time period. Every hour, the data for all available configuration files is regenerated for the last 13 months and stored on a shared drive so all are able to access the current data without even having to submit a request. A table is generated showing all warnings or errors produced during the data generation along with some metadata such as the data owner email in order for the data owner to quickly spot troublesome AWS.
Königshafen Submarine Groundwater Discharge Network (KiSNet) - first monitoring results from a multi-sensor and multidisciplinary approach
Authors: Mallast Ulf ,   KiSNet - Königshafen Submarine Groundwater Discharge Network
Published: March 2022

Submarine groundwater discharge (SGD) as a pathway for water and elements between land and ocean is a rather young topic and was for a long time neglected by the scientific community and coastal managers. However, the subject has increasingly attracted attention since the turn of the millennium. In this emerging field, measurement techniques and quantification methods strongly depend on individual research groups, but the high spatio-temporal variability of SGD, in general, leads to low confidence in its estimates at a regional scale.

The Königshafen Submarine Groundwater Discharge Network (KiSNet) seeks to form an interdisciplinary group of SGD experts to initiate and intensify collaborative ties across research groups. The aim is to bring together various methods from all disciplines to a common enclosed study area, Königshafen bay in Sylt, Germany. The strategy of measuring simultaneously results in a) a reliable groundwater picture of the bay, but also b) the possibility to suggest optimal combinations for qualitative and quantitative SGD methods that may serve as basis for a future more standardized SGD research.

Here we present first results from remote sensing, marine and terrestrial ground-based geophysics, seepage meters, temperature rods, natural tracers, numerical simulation from terrestrial and marine disciplines, and outline a preliminary concept of synergetic method combinations.
Unsupervised detection and quantification of iceberg populations within sea ice from dual-polarisation SAR imagery
Authors: Evans Ben , Fleming Andrew , Faul Anita , Hosking Scott , Lieser Jan , Fox Maria
Published: March 2022

Accurate estimates of iceberg populations, disintegration rates and iceberg movements are essential to fully understand ice sheet contributions to sea level rise and freshwater and heat balances. Understanding and prediction of iceberg distributions is also of paramount importance for the safety of commercial and research shipping operations in polar seas. Despite their manifold implications the operational monitoring of icebergs remains challenging, largely due to difficulties in automating their detection at scale.  

Synthetic Aperture Radar (SAR) data from satellites, by virtue of its ability to penetrate cloud cover and strong sensitivity to the dielectric properties of the reflecting surface, has long been recognised as providing great potential for the identification of icebergs. Many existing studies have developed algorithms to exploit this data source but the majority are designed for open water situations, require significant operator input, and are susceptible to the substantial spatial and temporal variability in backscatter characteristics within and between SAR scenes that result from meteorological, geometric and instrumental differences. Further ambiguity arises when detecting icebergs in dense fields close to the calving front and in the presence of sea ice. For detection to be fully automated, therefore, adaptive iceberg detection algorithms are required, of which few currently exist. 

Here we propose an unsupervised classification procedure based on a recursive implementation of a Dirichlet Process Mixture Model that is robust to inter-scene variability and is capable of identifying icebergs even within complex environments containing mixtures of open water, sea ice and icebergs of various sizess. The method exploits freely available dual-polarisation Sentinel 1 EW imagery, allowing for wide spatial coverage at a high temporal density and providing scope for near-real-time monitoring.  It overcomes many of the limitations of existing approaches in terms of environments to which it may be applied as well as requirements for labelled training datasets or determination of scene-specific thresholds. Thus it provides an excellent basis for operational monitoring and tracking of iceberg populations at a continental scale to inform both scientific and navigational priorities. 