bluuebunny/crossref_metadata_2025 huggingface dataset:
Reconstructing abrupt climate changes of the last deglaciation & Holocene: Pollen & biomarker analyses from the Portuguese Margin
Authors: Cutmore Anna , Ausin Blanca , Eglinton Timothy , Maslin Mark , Tzedakis Chronis
Published: March 2020

In light of the current rate of anthropogenic climate change, it is becoming increasingly critical to enhance knowledge of past abrupt climate events and subsequent responses of the Earth system. One period that can provide such insight is the last ~28 kyr, with several abrupt changes occurring over the course of the deglaciation. The Portuguese Margin has been an ideal location to study the impacts of these abrupt climate events on marine and terrestrial environments.  The combined effect of the narrow continental shelf and close proximity to the Tagus and Sado rivers, lead to the rapid delivery of a high quantity of sediment, including our pollen and biomarker proxies, to the Tagus Abyssal Plain. Joint terrestrial and palaeoceanographic analyses from the same sediment samples enable an in situ assessment of the relative timing of changes in palaeoceanographic and terrestrial proxies.

 

Here we document the response of western Iberian vegetation to millennial and centennial-scale changes, particularly changes in moisture availability, over the deglaciation and Holocene, by combining (for the first time at a Portuguese Margin site) pollen and leaf-wax isotopic biomarker records (δ13C and δD) from core SHAK06-5K. A high-resolution pollen record (every 2cm) and lower-resolution n-alkane δ13C and δD records spanning 28kya are compared with high-resolution XRF sediment and planktonic foraminiferal d18O analyses from the same core.  The sequence is supported by high-resolution age control, based on 40 Accelerator mass spectrometry (AMS) 14C dates from monospecific samples of the planktonic foraminifera, Globigerina bulloides.

 

Our pollen record indicates the rapid response of regional vegetation to centennial changes and millennial-scale climate events, with forest expansion during the warm interglacial/ interstadial Bølling-Allerød and Holocene, and forest contraction and steppe expansion during cold glacial/ stadial conditions of the Last Glacial Maximum and Younger Dryas. Comparing our pollen and n-alkane biomarker data with the XRF Zr:Sr ratio and planktonic foraminiferal δ18O records, a clear synchroneity can be seen in the timing of millennial-scale changes in all records.  The millennial-scale changes in our leaf wax n-alkane δD and δ13C records can be explained by both vegetation composition and growing season water availability. 
Effect of finite correlation time on the wave-particle interactions of nonlinear electrostatic structures with electrons in the Earth's radiation belts.
Authors: Osmane Adnane
Published: March 2020

In situ measurements of electron scale fluctuations by the Van Allen Probes and MMS have demonstrated the ubiquitous occurrence of phase-space holes and various kinetic nonlinear structures in the Earth's magnetosphere. However it remains an open question whether phase-space holes have to be incorporated into global magnetospheric models describing the energisation and acceleration of electrons. In this communication we will review current wave-particle models of electron phase-space holes interacting with energetic electrons (e.g. >1 keV in the Earth's radiation belts)  and present new theoretical results showing that finite correlation times of phase-space holes results in enhanced pitch-angle scattering. The pitch-angle scattering by phase-space holes is shown to be on par with that produced by chorus waves, and in some instances outgrows the chorus contribution. 

 
Pacific Meridional Overturning Circulation during the Mid-Pliocene Warm Period
Authors: Ford Heather L. , Burls Natalie , Hodell David
Published: March 2020

Today in the North Pacific only intermediate water forms because of a strong halocline, but Pacific Meridional Overturning Circulation (PMOC) may have existed in the past. The mid-Pliocene warm period (3.264-3.025 Ma) is a time of sustained warmth where atmospheric carbon dioxide concentrations were similar to today and the northern hemisphere was relatively ice free – making it a pseudo-analogue for future climate change. North Pacific sedimentological and climate modeling evidence suggests a PMOC formed during this time.  To determine the spatial extent of a PMOC during the mid-Pliocene warm period, we constructed a depth transect of sites between 2400 to 3400 m water depth on Shatsky Rise by measuring stable isotopes of Cibicidoides wuellerstorfi. We compare these new results with previously published records and calculate anomalies using the OC3 water column and core-top data products. The δ13C spatial pattern is consistent with a modest PMOC of intermediate depth (core ~2000 m) extending to the equator during the mid-Pliocene warm period. Ventilation of the North Pacific by a PMOC has broad implications for deep ocean carbon storage as the North Pacific contains the oldest, carbon-rich waters today. Future work will include minor and trace element analyses to determine the temperature and carbon characteristics of the PMOC water mass and comparisons with PlioMIP modeling outputs.
Fire severity and tree/forest structures derived from pre- and post-fire LiDAR data in a large forest fire in SE Spain
Authors: Viedma Olga , Moreno José M.
Published: March 2020

Heterogeneous patterns of trees and openings in forests create a patchy fuel matrix that may burn with different fire severity, which can affect post-fire regeneration. Understanding how forest structures determines fire severity and whether fire severity metrics entails variability in such structures within a given category is important to improve our ability to assess post-fire forest development. Here, we assessed how fire severity changes the vertical and horizontal structure of trees and forest stands, and what are the main post-fire tree/forest structures associated with different fire severities. The study site was a large and mixed severity fire (3,217 ha) occurred in southeast Spain (Yeste, Albacete) in the summer of 2017. Pre-fire forest structures were estimated from LiDAR data (sensor ALS 50 – II) collected in 2016, with a theoretical laser pulse density between 0.5-2 returns m2. Post-fire forest structures were estimated from LidarPod data (sensor Velodyne HDL-32e), with a laser pulse density of 312 returns m2, collected in April 2018 (8 months after fire) at 3 burned sites plus one unburned control. Fire severity was estimated from the post-fire NBR (Normalized Burn Ratio) and other similar indices derived from Sentinel 2. We found that up to 5 post-fire tree classes and up to 4 forest stand structures were separable, each characterized by different heights, gap fractions, crown properties and fire intensities. There was not a one-to-one relationship between tree/forest structures and standard fire severity levels. The main changes in height, crown and other tree properties were highly correlated with post-fire tree structures and fire severity indices. Accordingly, the trees more severely burned were those with higher losses in height and crown area. Our results indicate that satellite fire severity metrics were highly related to biomass consumption; nonetheless, standard fire severity classifications included several tree/forest structures that without Lidar data it would be impossible to differentiate.
Tracing Heavy Metals at Nantymwyn, Wales
Authors: Brown Aaron M.L. , Robertson Iain , Walsh Rory P.D. , Byrne Patrick , Edwards Paul , Williams Tom , De-Quincey Heather
Published: March 2020

Wales has a long history of coal and metal mining, with over 1,300 abandoned metal mines across the country. These mines pollute a number of rivers and lead to the failure of Water Framework Directive (WFD) standards for heavy metals. This includes Nantymwyn, an abandoned lead mine, which has two streams that flow into the River Tywi, and metal loads can be traced downstream for 65km. Nantymwyn, in common with many of Wales’ lead mines, has complex and poorly understood underground workings, which have degraded in the 90 years since closure. The mine is believed to have been worked during pre-Roman times and, is noted historically from AD 1530. The Nant y Bai stream flows through extensive spoil heaps, as well as over old workings, and has inflows from adits, over ground and subterranean inputs. Consequentially, conventional spot sampling of the metal concentrations as has been historically carried out by government agencies does not accurately convey the problems caused by the mine.

Tracer dilution and synoptic sampling was determined at Nantymwyn in July 2019 to calculate stream flow and heavy metal loadings and their variation downstream. Sodium bromide was injected upstream of the mine site, and once it reached a ‘plateau state’ in the stream it was sampled at 34 points over the 2km of stream. These samples were analysed for metal and bromide concentrations using Inductively coupled plasma mass spectrometry (ICP-MS), which allowed One-Dimensional Transport with Inflow and Storage (OTIS) modelling to predict pollutant flows. Additionally, monthly sampling and salt dilution flow gauging at 12 sites along the stream has been conducted since February 2019. The second, smaller stream at Nantymwyn is monitored monthly at six points.

Preliminary results show a large temporal variation in flows and concentrations across both streams, with varying loads of lead, but a consistent zinc load in the smaller stream. Initial results from the synoptic sampling show flows consistent with the salt gauging carried out after the stream had been sampled. This research will determine the extent of unseen inflow and outflows upon metal pollution on the River Tywi and allow mitigation strategies to be evaluated.
Cost and benefit analysis of Low Impact Development (LID) for stormwater management in an urban catchment in Norway
Authors: Xu Chong-Yu , Li Hong
Published: March 2020

There has been a surge of interest in the field of urban flooding in recent years, due to the growth of cities and the increase in frequency and magnitude of extreme rainfall events. Hydrological modeling is a useful tool to understand urban floods and compare different stormwater management solutions. In this study, we use the Storm Water Management Model (SWMM) in an urban catchment, Grefsen in Norway, to analyze the effects of different Low Impact Development (LID) methods to reduce combined sewer overflow (CSO). Additionally, we examine the cost of these solutions and find an optimized solution in terms of maximum effects and minimum cost. The results are useful for decision-makers to achieve sustainable stormwater management.

 

Acknowledgement:

This research is funded by the Norwegian Research Council via the project New Water Ways.
Nitrogen removal from waste rock drainage in northern Sweden with denitrifying woodchip bioreactor
Authors: Herbert Roger , Hellman Maria , Hallin Sara
Published: March 2020

Although nitrogen is not a traditional contaminant when considering the detrimental impacts of mine waste leachate on aquatic ecosystems, it is a common pollutant of concern in underground iron ore mining where waste rock leachate has a neutral pH and a low metal content. This is the case in northern Sweden, where environmental authorities, supported by the EU Water Framework Directive, have imposed strict regulations on nitrogen discharges to oligotrophic surface water systems. Requirements for lower nitrogen releases has driven the development and application of a bioreactor technology for nitrate removal at LKAB’s Kiruna iron ore mine.

A full-scale woodchip denitrifying bioreactor has been in operation since September 2018 in Kiruna for the removal of nitrate (NO3-) from waste rock leachate. Drainage from the waste rock pile is intercepted in a subsurface groundwater collection reservoir at the toe of the waste rock pile and pumped at an average rate of 22 m3/d into the bioreactor. Leachate from the low-sulfur waste rock is characterized by neutral pH (average pH 7), moderate alkalinity (108 mg/L HCO3-), and elevated concentrations of sulfate, NO3- and chloride (average concentrations 670, 61 and 102 mg L-1 respectively).

During 2019, and average nitrogen removal efficiency was 77%: during the 165 day sampling period, 189 kg NO3-N were removed in the bioreactor, which is primarily attributed to denitrification. A net production of 26 kg of NO2-N was measured. Nitrous oxide (N2O) emissions in gas and aqueous phase are low from the bioreactor and the primary product of denitrification is assumed to molecular nitrogen (N2). Dissolved N2O concentrations were on average greater at the bioreactor inlet (277 µg L-1) than at the outlet (179 µg L-1), although variations were substantial during the summer months with a net dissolved N2O export from the bioreactor on one occasion in late summer. The flux as N2O from the bioreactor surface varied from 1 – 28 mg N2O m-2 d-1. In addition to nitrate removal, zinc concentrations were reduced by, on average, 88%. 
The RHOSSA campaign: Multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack
Authors: Calonne Neige , Richter Betti , Löwe Henning , Cetti Cecilia , Ter Schure judith , Van Herwiijnen Alec , Fierz Charles , Jaggi Matthias , Schneebeli Martin
Published: March 2020

The necessity of characterizing snow through objective, physically-motivated parameters has led to new model formulations and new measurement techniques. Consequently, essential structural parameters such as density and specific surface area (for basic characterization) or mechanical parameters such as the critical crack length (for avalanche stability characterization) gradually replace the semi-empirical indices acquired from traditional stratigraphy. These advances come along with new demands and potentials for validation. To this end, we conducted the RHOSSA field campaign, in resemblance of density (ρ) and specific surface area (SSA), at the Weissfluhjoch research site in the Swiss Alps to provide a multi-instrument, multi-resolution dataset of density, SSA, and critical crack length over the complete winter season 2015-2016. In this paper, we present the design of the campaign and a basic analysis of the measurements alongside with predictions from the model SNOWPACK. To bridge between traditional and new methods, the campaign comprises traditional profiles, density cutter, IceCube, SnowMicroPen (SMP), micro-computed-tomography, propagation saw tests, and compression tests. To bridge between different temporal resolutions, the traditional weekly to bi-weekly snow pits were complemented by daily SMP measurements. From the latter, we derived a re-calibration of the statistical retrieval of density and SSA for SMP version 4 that yields an unprecedented, spatio-temporal picture of the seasonal evolution of density and SSA in a snowpack. Finally, we provide an inter-comparison of measured and modeled estimates of density and SSA for 4 characteristic layers over the entire season to demonstrate the potential of high temporal resolution monitoring for snowpack model validation.
Quantification of initiating events probability based on fragility functions and Bayesian network applied for multi-hazard
Authors: Kaszko Aleksej , Kowal Karol , Potempski Sławomir
Published: March 2020

There are many ways to quantify initiating event probability and most of them are described in document “Defining initiating events for purposes of probabilistic safety assessment”, developed by the International Atomic Energy Agency . This guide describes seven methods: engineering evaluation or technical study of plant; reference to previous probabilistic safety assessment; EPRI list of initiating events; logical classification; plant energy balance fault tree; analysis of operation experience for actual plant; failure mode and effect analysis. In practice, currently many of PSA specialists use EPRI list of IEs, which has been originally prepared for single hazard and application to multiple hazards is not straightforward. Therefore other approaches are considered. In the paper combined method based on fragility functions and Bayesian network is proposed in order to elaborate for easier and more accurate approximation of the probability of initiating events caused by multiple hazards. In this respect, first of all, events fragility functions for hazards considered or multi-hazard fragility function are needed, which can have various form like , for example, parameterized fragility functions or logit fragility function. The next step is to develop a model the Bayesian network with the implementation of derived fragility functions. This can be performed using widely available computing programs for interactive building Bayesian network models .Depending on the hazards considered, the Bayesian network should be then developed accordingly. Example of such Bayesian network will be given.

Finally after calculating the probability of initiating events using this combined method, the results can be used in Event Trees and Fault Trees already developed for considered nuclear installation, in order to update the estimations of probabilities. Such an approach has also practical meaning as it will reduce man-month costs in comparison with the approach based on building full PSA models in Bayesian network.
CMEMS Primary production from satellite remote sensing: spatial and temporal evolution and comparison with other products
Authors: Bretagnon Marine , Garnesson Philippe , Mangin Antoine
Published: March 2020

Half of the global primary production is produced in the ocean by phytoplankton and the reaction of photosynthesis. For the marine environment, primary production is at the basis for the food web, by the supply of energy for higher trophic levels. Monitor primary production appears therefore to be a guideline to reach sustainable fisheries. In addition to its role on the trophic web, primary production is also important for its role on CO2 fluxes. Indeed, while phytoplankton creates matter from nutrients and CO2. The produced matter can be grazed by higher trophic levels or sink towards sediment. Amount of carbon sequestrated and exported out of the productive layer give some clues efficiencies of the oceanic biological carbon pump. Primary production is therefore important not only for economic resources, but also for climatic studies, to investigate if the ocean is a carbon sink or sources.

A strategy of algorithm validation / inter-comparison was used as part as the CMEMS project to identify most accurate primary production algorithm among the most used in the literature.

Primary production validation is based on the commonly used comparison with in situ data, as well as the frequency and the intensity of the annual bloom in different basin. Inter-comparison with model were performed at the basin scale of the Mediterranean Sea to assess the robustness and the consistency of different type of estimates.

Satellite estimate of primary production, as proposed by CMEMS, give now access to an archive of 21 years for user community, to investigate evolution of primary production at the global scale or in specific basin.

 
Habitat mapping and change assessment of coastal wetlands by using Sentinel-2 time series and ecological expert knowledge
Authors: Adamo Maria , Tomaselli Valeria , Mantino Francesca , Tarantino Cristina , Blonda Palma
Published: March 2020

Coastal wetlands are one of the most threatened ecosystems worldwide. In the Mediterranean Region, wetlands are undergoing rapid changes due to the increasing of human pressures (e.g. land reclamation, water resources exploitation) and climate changes (e.g. coastal erosion), with a resulting habitat degradation, fragmentation, and biodiversity loss.

Long-term habitat mapping and change detection are essential for the management of coastal wetlands as well as for evaluating the impact of conservation policies.

Earth observation (EO) data and techniques are a valuable resource for long-term habitat mapping, thanks to the large amount of available data and their high spatial and temporal resolution. In this study, we propose an approach based on the integration of time series of Sentinel-2 images and ecological expert knowledge for land cover (LC) mapping and automatic translation to habitats in coastal wetlands. In particular, the research relies on the exploitation of ecological rules based on combined information related to plant phenology, water seasonality of aquatic species, pattern zonation, and habitat geometric properties.

The methodology is applied to two Natura2000 sites, “Zone umide della Capitanata” and “Paludi presso il Golfo di Manfredonia”, located in the northeastern part of the Puglia region. These two areas are the most extensive wetlands of the Italian peninsula and the largest components of the Mediterranean wetland system.

Land Cover classes are labelled according to the FAO-LCCS taxonomy, which offers a framework to integrate EO data with in situ and ancillary data. Output habitat classes are labelled according to EUNIS habitat classification.
Landscape-driven carbon export from small coastal permafrost watersheds
Authors: Speetjens Niek , Tanski George , Martin Victoria , Wagner Julia , Richter Andreas , Hugelius Gustaf , Lodi Rachele , Knoblauch Christian , Koch Boris , Stedmon Colin , Vonk Jorien
Published: March 2020

Ongoing climate warming in the western Canadian Arctic is leading to thawing of permafrost soils and subsequent mobilization of its organic matter (OM) pool. Part of this mobilized terrestrial OM enters the aquatic system as dissolved organic matter (DOM) and is laterally transported from land to sea. Mobilized DOM is an important source of nutrients for ecosystems as it is available for microbial breakdown, the consequent turnover of the dissolved organic carbon (DOC) fraction of DOM serving as a potential source of greenhouse gases. We are beginning to understand spatial controls on the release of DOM as well as the quantities and fate of this material in large arctic rivers, but these processes remain systematically understudied in small, high-arctic watersheds, despite the fact that these particular watersheds experience strongest warming.

We sampled soil (active layer and permafrost) and water (porewater and stream water) from two small catchments along the Yukon coast, Canada, during the summers of 2018 and 2019. We assessed the organic carbon quantity (using DOC and soil OC content), quality (d13C-DOC, C/N ratios and optical properties including components modelled with EEMs-PARAFAC), the turnover of DOM through incubation experiments as well as nutrients and stable water isotopes. We classify and compare different landscape units by quantitative and qualitative change across gradients from soil stocks down to the catchment outflow.

Our results show that substantial variation in DOC concentrations exists among various landscape units as well as between active layer and permafrost. We find high soil carbon stocks and leaching potentials from these coastal tundra soils. Moreover, we find that permafrost DOM is utilized rapidly upon thaw. Using remote sensing-based landscape classification, we are planning to upscale carbon and nutrient fluxes for the panarctic coastal zone to account for small yet numerous high-arctic watersheds in lateral terrestrial OM transfer from land to sea Under current climate projections and with continued permafrost thaw altered lateral fluxes may have profound impacts on the arctic aquatic ecosystem and arctic carbon cycling.
Spatiotemporal dynamics of land development intensity and summertime extreme surface urban heat island effect in Greater Shanghai (1990-2017)
Authors: Zhang Hao , Dai Xiao-yan
Published: March 2020

Greater Shanghai, one of China’s top megacities, is susceptible to extreme heat events during the summer. This study investigated the spatiotemporal dynamics of land development intensity and its influence on summertime extreme surface urban heat island (SUHI) effect in Greater Shanghai, during 1990 and 2017. Driven by the robust economic development and population growth, the formation of Greater Shanghai has dramatically changed from a traditionally compact city to an explosively urbanizing region in 1990–2017. The results revealed an overall increase in regional LDI of Greater Shanghai in the loss of cropland and water bodies. Simultaneously, the intensified SUHI effect was measured by the increasing relative SUHI intensity (from 1.81℃ in 1990 to 3.16℃ in 2017) and magnitude (from 306.80 km2 in 1990 to 1570.56 km2 in 2017). The urban-rural gradient analysis based on centric buffers and the representative transects further revealed the spatiotemporal heterogeneity of LDI and its linkage with the evolutionary pattern of the SUHI effect. As indicated, the areal extent of downtown Shanghai within the 0–15 km buffer increased by 201.70 km2 in 1990–2017. However, its stably decreasing trends in LDI and associated SUHI effect were observed across the study period. In contrast, the urban periphery and exurban area, which attracted huge investment to develop the infrastructure required for population resettlement and the industrial restructure, experienced a dramatic increase in 1660.57km2 of newly developed land. Concurrently, the remarkably increases in LDI and associated SUHI effect the urban periphery and exurban area were notable. Finally, focusing on the overall alarming situation of the summertime SUHI effect in Greater Shanghai, policy implications, and practical suggestions towards sustainable land development and UHI mitigation were discussed.   
Drought stress detection with a coupled AgroC-SCOPE model
Authors: De Cannière Simon , Herbst Michael , Jonard François
Published: March 2020

Photosynthesis is the cornerstone of all life on earth. Light energy, captured by chlorophyll, fuels photosynthesis. As an excess of absorbed light leads to harmful products, the excess light is either dissipated as heat or it is re-emitted in the atmosphere. The latter pathway results in a weak, but very specific spectral signal, right from the heart of the photosynthetic apparatus, called chlorophyll fluorescence. Recent advancements in spectrometry have allowed the retrieval of fluorescence with remote sensing. Given its close link to photosynthesis, it has the potential of informing crop growth models. The aim of this study is to estimate the stress parameter of the crop growth model AgroC by incorporating remotely-sensed sun-induced chlorophyll fluorescence (SIF) data. The radiative transfer model SCOPE converts the leaf-level fluorescence obtained from AgroC to canopy-scale SIF. In case of a stress, the SIF at 760 nm decreases, while the SIF at 687 nm shows a more complex relationship to stress. Comparing the modelled canopy-scale and observed SIF provides information on the plant water stress status, allowing a more precise estimate of the photosynthetic activity. Downstream, this leads to a better estimation of the plant growth, as well as a better estimation of the carbon and water fluxes. A field campaign is conducted over a sugar beet field in Merzenhausen, Germany, in which the fluorescence was measured alongside the water and carbon fluxes. As the fluorescence provides an additional constraint on the photosynthesis, the AgroC-SCOPE model is expected to provide significantly better estimates of the carbon fluxes compared to the AgroC model. The results of the coupled AgroC-SCOPE model will be presented at this meeting. This study provides information on the link between drought stress and fluorescence. An approach similar to the one proposed in this study will allow detecting drought stress at the regional to global scale with FLEX data.
Integrating citizen science, open and big data into water and environmental decision support systems
Authors: Monacelli Giuseppina , Cipolloni Carlo , Babbini Lorenza , Sole Maria Chiara , Lotti Alessandro , Annis Antonio , Spasiano Andrea , Nardi Fernando
Published: March 2020

Water and environmental monitoring, observation and decision support systems (DSS) are being transformed by a wealth of open and big data that are increasingly available, accurate and timely. Consolidated technologies of earth observation, remote sensing, geospatial modelling and visualization systems are stimulating earth, hydrological and environmental sciences that are reacting not only with increasing scientific production, but with novel solutions-oriented methods, tools and algorithms. Procedures, methods and tools are more and more available for analysis, interpretation and mapping of river and basin coastal landscape features and hydro-environmental dynamics. Citizen science are further empowering the capabilities of DSS by gathering and sharing data on the human behaviour component to better understand the nature-human-urban interplay. Citizens, empowered by mobile devices, act as data and information producers, receivers and transmitters supporting the assessment of the effects of human-derived observations, feedbacks and actions sensing. Emerging hardware and software technologies (e.g. machine learning, artificial intelligence, IoT, etc.) are creating amazing opportunities for these DSS linked to the development of the human-machine interface and its use for promoting practical environmental and social actions to manage and mitigate natural hazard and climatic risks. The National System for Environmental Protection (SNPA) by the Italian Institute for Environmental Protection and Research (ISPRA) is supporting and implementing a wide and diverse range of research, applied research, learning and communication activities, both at the national and international level, in collaborating with leading academic, professional and international organizations, for integrating citizen science, open data and big data into next generation water and environmental decision support systems. This contribution, while depicting the overall SINA framework (Italian Environmental Information System) and ongoing and planned activities by ISPRA SNPA and SINA, presents recent outcomes of research initiatives developed within the Water JPI, UNEP INFORAC, National Plan for Climate Adaptation (PNACC), Marine pollution, Biodiversity, the Water, Food and Energy Nexus among others. Insights from joint research efforts and working groups are presented and shared while pursuing further synergies and stimulate the discussion on this crucial topic for national and international agencies, like ISPRA, that seek to transfer research data, models and tools into institutional and operational activities.
Sea ice representation in sea ice model of CICE and Icepack
Authors: Wang Caixin , Granskog Mats A. , Debernard Jens Boldingh , Wang Keguang
Published: March 2020

Sea ice is a critical component of the Earth system, playing an important role in high-latitude
surface radiation balance and heat, moisture and momentum exchange between atmosphere
and ocean. In recent years, rapid changes have been occurring in Arctic sea ice, including
decline in ice extent/area, decreasing in ice thickness and volume, and shifting towards a first-
year ice (FYI) dominated, rather than multi-year ice (MYI) dominated ice pack. These are one
of the most well-known and striking examples of climate change. However, representing
these changes in the model is still in question since most of our knowledge is based on MYI.
CICE is a sea ice model developed at Los Alamos National Laboratory since 1994. It is
widely used to simulate the growth, melt and movement of sea ice, and to resolve the
biogeochemical processes. Its column version, Icepack, has been separated from CICE after
CICE V5.1.2, which provides additional opportunity for simulating the evolution of drifting
sea ice floes. How about the representation of sea ice in a column model (Icepack) and a 3d
model (CICE)? In 2012, an ice mass balance buoy (IMB) and a Spectral Radiation Buoy
(SRB) were deployed on FYI near the North Pole, and later drifted towards Fram Strait. These
buoys collected a complete summer melt season of in-band (350-800 nm) spectral solar
radiation and sea ice mass balance data. In this study, we apply the Icepack (version 1.1.1)
and CICE (version 5.1.2) to investigate the seasonal evolution of sea ice in 2012 in these two models, and
assess how well the physical processes are represented in CICE and Icepack, with the focus
on the surface changes.
Determination of the Isotopic Composition of Iridium Using Multicollector-ICPMS
Authors: Zhu Zuhao
Published: March 2020

Like many other elements, iridium is lacking a calibrated, SI traceable isotope ratio measurement. In this study, we
have undertaken absolute isotope amount ratio measurements of iridium by multicollector inductively coupled plasma mass
spectrometry (MC-ICPMS) using a state-of-the-art regression model to correct for the instrumental fractionation (mass bias) of
isotope ratios using both NIST SRM 997 isotopic thallium and NIST SRM 989 isotopic rhenium as primary calibrators. The
optimized regression mass bias correction model is based on incrementally increasing plasma power and short (10−30 min)
measurement sessions. This experimental design allows fast implementation of the regression method which would normally
require hours-long measurement sessions when executed under constant plasma power. Measurements of four commercial
iridium materials provide a calibrated iridium isotope ratio R193/191 = 1.6866(6)k=1 which corresponds to isotopic abundance x191
= 0.372 21(8)k=1 and an atomic weight of Ar(Ir) = 192.217 63(17)k=1. In addition, we present data on a new Certified Reference
Material from NRC Canada IRIS-1 which fulfills the requirements of a delta zero reference for iridium isotope ratio
measurements.
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle
Authors: Michot Veronique , Brogniez Helene , Vrac Mathieu , Thao Soulivanh , Chepfer Helene , Yiou Pascal , Dufour Christophe
Published: March 2020

The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a major issue for the understanding of the atmospheric water cycle. At present, these interactions are poorly known at regional and local scales, i.e. within 100km, and are therefore poorly represented in numerical climate models. This is why we have sought to predict cloud scale relative humidity profiles in the intertropical zone, using a non-parametric statistical downscaling method called quantile regression forest. The procedure includes co-located data from 3 satellites: CALIPSO lidar and CloudSat radar, used as predictors and providing cloud properties at 90m and 1.4km horizontal resolution respectively; SAPHIR data used as a predictor and providing relative humidity at an initial horizontal resolution of 10km. Quantile regression forests were used to predict relative humidity profiles at the CALIPSO and CloudSat scales. These predictions are able to reproduce a relative humidity variability consistent with the cloud profiles and are confirmed by values of coefficients of determination greater than 0.7, relative to observed relative humidity, and Continuous Rank Probability Skill Score between 0 and 1, relative to climatology. Lidar measurements from the NARVAL 1&2 campaigns and radiosondes from the EUREC4A campaigns were also used to compare Relative Humidity profiles at the SAPHIR scale and at the scale of forest regression prediction by quantile regression.
GINGERINO and the GINGER Project
Authors: Di Virgilio Angela D. V.
Published: March 2020

GINGER (Gyroscopes IN General Relativity) is a proposal aiming at measuring the Lense-Thirring effect with an experiment based on Earth. It is based on an array of ring lasers, at present the most sensitive inertial sensors to measure the rotation rate of the Earth.

Rotation and angular measurements are of great importance for various fields of science: General Relativity predicts rotation terms originated from the kinetic term, Earth Science studies the Earth's angular velocity with its variations, the tides and related perturbations, the normal modes of the Earth, the angular perturbations associated to the movement of the plates, the deformations of hydrological nature, without neglecting the rotational signals produced by the earthquakes. A ring laser integral to the Earth's surface is sensitive not only to the angular rotation of the planet, but also to global and local rotational signals. For this reason GINGER is relevant for geophysics.

GINGERINO is a ring laser prototype installed inside the underground laboratory of the Gran Sasso. Its typical sensitivity is well below 0.1 nrad/s in 1 second measurement, and it is acquiring data on a continuous basis since several years. The most recent data of GINGERINO and the results relevant for geoscience are discussed.
In situ measurements of coupled wind-wave dynamics using PIV
Authors: Buckley Marc , Horstmann Jochen
Published: March 2020

Small-scale turbulent dynamics within the coupled atmospheric and oceanic wave boundary layers control air-sea fluxes of momentum and scalars. However measuring and understanding small-scale dynamics very close to the rapidly moving ocean surface remains technically challenging.

We present novel in situ measurements of small-scale motions in the airflow above, and in the water below the wavy air-water interface. A high resolution, large field of view PIV system (Particle Image Velocimetry) was developed for in situ air-water measurements within the first millimeters to meters above and below the wavy surface. The system was recently deployed on a single pile platform in the Szczecin lagoon (Baltic Sea coast, Germany). We will show first results and we will discuss the influence of waves on the partitioning of momentum flux within the coupled air-water wave boundary layers.
Sea Surface Wind Speed Estimation based on USV borne System by BDS Reflectometry
Authors: Chen Yanling , Wu Jianming , Guo Peng , Wang Xiaoya
Published: March 2020

Previously ship-borne GNSS-R (Global Navigation Satellite System Reflectometry) experiments have been carried out on the Kiloton scientific research vessel or above with relatively stable attitude. In this paper, we developed a GNSS-R platform based on the unmanned surface vessel(USV) for the first time, whose main functions include receiving, storing and processing BDS(BeiDou navigation satellite system) direct and reflected signal. In order to overcome the affect of rapidly changed attitude of the small ship, we designed and installed a three axis stabilizer to keep the antenna stable. Meanwhile, we made full use of the geostationary characteristics of BDS GEO satellite, and calculated the interference complex field (ICF) between the direct and reflected signal so as to estimate sea wind speed near the track of USV. The case study in Hengsha Island, Shanghai from June 9 to 11, 2019 showed that the RMS of wind speed is better than 0.50m/s by comparison with the hot-film anemometer measurement.

Key words: Wind speed; unmanned surface vessel; attitude;  BDS Reflectometry; hot-film anemometer

Acknowledgements:  This work is supported by Natural Science Foundation of Shanghai (No. 17ZR1435700), National Natural Science Foundation of China project (No. 41074019) and State Key Laboratory of Estuarine and Coastal Research, East China Normal University.
A data-driven statistical approach for flood hazard zoning at national scale
Authors: Marchesini Ivan , Rossi Mauro , Salvati Paola , Donnini Marco , Sterlacchini Simone , Guzzetti Fausto
Published: March 2020

The delimitation of flood-prone areas is an important non-structural measure that proves to be effective in the long term in reducing food risk.

In Italy, more than 20 basin’s Units of Management (UoMs) were in charge to delineate the flood hazard zoning (FHZ) for three different flood return periods. Mostly, FHZ was prepared using physically based models i.e., considering the rainfall-runoff transformation and simulating the flood discharge through the river network. Physically-based models require many inputs and boundary conditions including: hydro-meteorological data, detailed characterization of the geometry of the riverbeds, roughness, infiltration parameters and also real hydrometric measurements in order to be calibrated. Physically based modelling is therefore a long, time consuming and resource intensive process that should be frequently updated to take into account the river channel changes. As a consequence, the Italian FHZ suffers from an underlying lack of homogeneity across the different UoMs, resulting in significant differences on the percentage of the river network for which the flood-prone areas were delineated.

As alternatives to physically based models, in recent years many authors have produced maps of flood susceptibility or hazard using expert (e.g. Analytic Hierarchy Process) or data-driven (e.g.  multivariate statistics or machine learning) approaches. Such methods were mostly used in ungauged territories where hydro-meteorological data is not available.

Here we present a procedure, named Flood-SHE (Flood - Statistical Hazard Evaluation), which is aimed at the delineation of flood-prone areas and the corresponding expected water depth, using a multivariate statistical classification model. Flood-SHE was applied to the entire Italian territory with the aim to integrate the UOMs FHZ where it is not available or incomplete. The classification model was trained exploiting the existing UoMs FHZ and using, as independent variables, a set of geomorphometric layers (derived at 10x10 meters ground resolution) which includes the distance and height to the closest rivers and to the basins outlets, the local DEM slope, a stream order classification criterion and the DEM local roughness. Random training and validation areas were used for the classification model in order to obtain an estimation of the uncertainty of the values of the predictive performance indexes. Results highlight (i) the significance of the the variables distance and height to the closest rivers, roughness and stream order in predicting the flood-prone areas, (ii) the impact of the UoMs morphology and the quality of UoMs FHZ on the reliability of the statistically modeled flood-prone areas.
Analysis of specific water masses transports in the Western Mediterranean in the MEDRYS1V2 twenty-one-year reanalysis.
Authors: Barral Quentin-Boris , Zakardjian Bruno , Dumas Franck , Garreau Pierre , Beuvier Jonathan
Published: March 2020

We present an analysis of specific water masses fluxes in the Western Mediterranean Sea issued from a twenty years (1992-2013) reanalysis (MEDRYS1V2). Water masses are identified on the base of salinity and potential density properties and computes; the fractions of each water mass involved in total flux are computed under the hypothesis assumptions of mixing lines schemes. It was first designed in order to avoid rough truncations between water masses on the T-S diagram when using fixed thermo-haline properties thresholds. The method does not use the temperature marker due to its high seasonal variability in near surface waters (0-200 m) and we consider that potential density is a better marker to discriminate deep and intermediate water masses. The algorithm discriminates successively five different water masses : the Atlantic Water (AW) incoming from the Gibraltar strait (salinity between 36,1 and 38,45 PSU), the Levantine Intermediate Waters (LIW) incoming from the Tunisia-Sicily strait (salinity between 38,45 and 39.1 PSU), the Modified Atlantic Waters (MAW) defined as near-surface waters (potential density less than 28,9 kg m-3) that are neither AW or LIW, while Western Intermediate Waters (WIW) are those remaining until the σθ = 29,10 kg m-3 threshold for Western Mediterranean Deep Waters (WMDW) is reached. Such computed fractions of each water mass, whose sum is constrained to unity, are then used to compute their water masses transports all along over twenty years of the reanalysis. The transport are assessed across computed on key transects delimiting known sub-basin entities (Ligurian Sea, Gulf of Lion, Balearic Sea...), with total transports showing balanced mass budget. The such computed total transport reveal marked differences in their seasonal to interannual variability, while the analysis of the water mass transports allows to identify those which mainly implied induced these variability. The results first show a low seasonal and no significant interannual variability at the exit of the Alboran Sea that results from the balance between the eastward AW/MAW outflow and the westward WIW and WMDW inflows. The Corsican strait, the Ligurian Sea line and Tunisia-Sardinia straits show a marked seasonal variability (0,37-0,39 Sv) mainly driven by the AW/MAW. By contrast, a strong interannual variability dominates the seasonal one (-2 to 1 Sv) between the Algerian Basin and the northern basin, correlated to the WMDW formation. The analysis of each specific water masses transport pointed out that shows this marked variability to be first driven by the intermediate and deep water masses transports. Similarly the interannual variability of the AW and MAW transports in the central part of the Western Mediterranean suggests some coupling between the deep, intermediate and surface water masses, even through the shallower Balearic Sea.
SEW-REAP: planting the seeds of early career soil-soya research in China
Authors: Dodd Ian , Castro Pedro , Martinez-Melgarejo Purificacion , Perez-Alfocea Francisco , Tian Jian , Lam Hon-Ming , Zhang Jianhua , Tyfield David
Published: March 2020

SEW-REAP (Addressing food Security, Environmental stress and Water by promoting multidisciplinary Research EU And China Partnerships in science and business) was a European Union funded project (2016-2019) that placed European environmental researchers at Chinese institutions, in contrast to the more typical model of China Scholarship Council-funded visits of Chinese PhD students to the EU. These EU students were registered for their PhDs in European institutions, but conducted most of their research (18-24 months) in China. Since Chinese government policy is to become more self-sufficient in soya (Glycine max) production, and this crop provides a well-studied model system with significant genomic resources, two European students (PC and PMM) investigated variation in environmental stress responses (water deficit and phosphorus deficiency respectively) of diverse Chinese soya germplasm. PC identified significant variation in soya stomatal sensitivity to drying soil, which was related to variation in root-shoot signalling of the stress hormone ABA. PMM identified significant variation in soya root growth sensitivity to lack of phosphorus, which was related to variation in root accumulation of the stress hormone ABA. Whether variation in stomatal closure affects phosphorus transport to the shoot, and whether phosphorus-mediated changes in root growth affect root-to-shoot signalling of water deficit, needs to be investigated as different genotypic strategies may have antagonistic or complementary effects in multi-stress environments. Regardless of the physiological mechanisms involved in plant responses, SEW-REAP early career researchers have accessed complementary expertise across two continents to embrace a unique training opportunity and develop new scientific networks.