bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty assessment of climate impact indicators in future scenarios projections for water allocation in small catchments
Authors: Perez-Palazon María José , Herrera-Grimaldi Pascual , Pimentel Rafael , Polo María José
Published: March 2020

Climate services provide data dealing with future climate scenarios and projections. Climatic models ensemble mean is commonly used as the recommended value to assess climate change effects in impact studies. This ensemble is composed of different combinations of Global Circulation Models (GCM) and Regional Climate Models (RCM), not being a fixed number the quantity of RCM-GCM combinations needed to calculate this ensemble.  Recommendations found in literature indicate a range usually between 5 to 10 endmembers, but the suitability of some of the models is not always included in the assessment of the applications. How to choose correctly these number of models or to reduce its number is an issue currently under debate. In heterogeneous and/or small areas where the spatial significant scales cannot be adequately captured by coarse grids, climatic models often have problem to correctly represent hydrometeorological variables due to the GCM-RCM parameterizations. Moreover, some of these combinations give completely uneven simulated climate regime during the reference period and, consequently, hydrological variables like river flow are poorly simulated from these generated drivers.

This work proposes an alternative methodology to project hydrological variables without using model ensemble mean, selecting only the model that best represent climate regime, defining transfer functions to overpass the spatial scale issues, and assessing uncertainty by using stochastics techniques. The methodology is applied in the Guadalfeo River Basin, a mountainous semiarid watershed in Sierra Nevada (southern Spain), where alpine and Mediterranean climate coexist, and the highest summits of the Iberian Peninsula are located; hence,  snow plays a key role in the water availability and management, and future impacts are key to assess adaptation plans . The projected variables are used to assess changes in climatic impact indicators in future scenarios projections for water allocation for three different end-user sectors: small hydropower generation, water allocation in a reservoir system, coastal municipality dealing with water allocation conditioned by agriculture and tourism. 

 

This work was funded by the project AQUACLEW, which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Commission [Grant 690462].
Effective sampling of behavioral subsurface parameter realizations assisted by surrogate models
Authors: Erdal Daniel , Xiao Sinan , Nowak Wolfgang , Cirpka Olaf A.
Published: March 2020

Global sensitivity analysis and uncertainty quantification of nonlinear models may be performed using ensembles of model runs. However, already in moderately complex models many combinations of parameters, which appear reasonable by prior knowledge, can lead to unrealistic model outcomes, like perennial rivers that fall dry in the model or simulated severe floodings that have not been observed in the real system. We denote these parameter combinations with implausible outcome as “non-behavior”. Creating a sufficiently large ensemble of behavioral model realizations can be computationally prohibitive, if the individual model runs are expensive and only a small fraction of the parameter space is behavioral. In this work, we design a stochastic, sequential sampling engine that utilizes fast and simple surrogate models trained on past realizations of the original, complex model. Our engine uses the surrogate model to estimate whether a candidate realization will turn out to be behavioral or not. Only parameter sets that with a reasonable certainty of being behavioral (as predicted by the surrogate model) are simulated using the original, complex model. For a subsurface flow model of a small south-western German catchment, we can show high accuracy in the surrogate model predictions regarding the behavioral status of the parameter sets. This increases the fraction of behavioral model runs (actually computed with the original, complex model) over total complex-models runs to 20-90%, compared to 0.1% without our method (e.g., using brute-force Monte Carlo sampling).  This notable performance increase depends on the choice of surrogate modeling technique. Towards this end, we consider both Gaussian Process Emulation (GPE) and models based on polynomials of active variables determined by Active Subspace decomposition as surrogate models. For the GPE-based surrogate model, we also compare random search and active learning strategies for the training of the surrogate model.
How to interpret Holocene palaeoenvironmental and cultural changes in SW Iberia based on the palynological record from the GeoB23519-01 core (RV METEOR cruise M152)
Authors: Val-Peón Cristina , Eichner Daniela , López-Sáez José A. , Reicherter Klaus , Feist Lisa , Costa Pedro J.M. , Bellanova Piero , Santisteban Juan I. , Bosnic Ivana , Schwarzbauer Jan , Frenken Mike , Vött Andreas , Brückner Helmut , Schüttrumpf Holger , Andrade César , Duarte João F. , Kuhlmann Jannis
Published: March 2020

The southwest of the Iberian peninsula is, due to its border position between Africa and Europe, a key territory of major geoarchaeological interest, as well as a reservoir of biodiversity and a wildlife refuge area during the Holocene. Bioclimatic conditions have been significantly unstable during this period in the Western Mediterranean. Therefore, further studies are still required to understand how abrupt climate changes such as the 8.2 and 4.2 ka cal BP events impacted societies and environment.

 

In November 2018 the RV Meteor cruise M-152 retrieved 19 vibracores and 4 gravity cores along the Algarve coast after mapping the bathymetry. One of these cores, GeoB23519-01, was taken 65 m below present sea level and recovered 365 cm of sediment. Four potential event layers were identified over the last 11 ka cal BP and, at least two of them, are related to tsunami deposits (ca. 4370 cal BP and AD 1755).

 

This sedimentary archive was analysed in a multi-proxy approach, including palynological and micropalaeontological analyses, which allow characterizing palaeoenvironmental changes along the core. However, considering the characteristics of these deposits, we raise questions about how complex this palynological record is and how it mirrors some short-term events, climate dynamics, and cultural disruptions.
Monitoring permafrost changes in the Yangtze River source region of the Qinghai-Tibetan Plateau using differential SAR interferometry
Authors: Wang Lingxiao , Zhao Lin , Zhou Huayun , Liu Shibo , Huang Xiaodong , Wang Chong
Published: March 2020

Qinghai-Tibet Plateau (QTP) has the largest high-altitude permafrost zone in the middle and low latitudes. Substantial hydrologic changes have been observed in the Yangtze River source region and adjacent areas in the early 21st century. Permafrost on the QTP has undergone degradation under global warming. The ground leveling observation site near Tangula (33°04′N, 91°56′E) located in the degraded alpine meadow indicates that the ground has subsided 50mm since 2011. The contribution of permafrost degradation and loss of ground ice to the hydrologic changes is however still lacking. This study monitors the permafrost changes by applying the Small BAseline Subset InSAR (SBAS-InSAR) technique using C-band Sentinel-1 datasets during 2014-2019. The ground deformation over permafrost terrain is derived in spatial and temporal scale, which reflects the seasonal freeze-thaw cycle in the active layer and long-term thawing of ground ice beneath the active layer. Results show the seasonal thaw displacement exhibits a strong correlation with surficial geology contacts. The ground leveling data is used to validate the ground deformation monitoring results. Then, the ground deformation characteristics are analyzed against the landscape units. Last, the long-term inter-annual displacement value is used to estimate the water equivalent of ground ice melting.
A copula-based multivariate drought indicator to design and monitor nature-based solutions
Authors: Debele Sisay , Sahani Jeetendra , Porcù Federico , Aragão Leonardo , Spyrou Christos , Loupis Michael , Charizopoulos Nikos , Di Sabatino Silvana , Kumar Prashant
Published: March 2020

Abstract

Droughts are comprehensive and complex naturally occurring hazards in any climatic region around the world and often result in the loss of life and severe ecosystem damage. Drought monitoring is usually based on single-variables that may not represent the corresponding risk appropriately to its multiple causation and impact characteristics under current and future climate scenarios. In order to address this issue, the multidimensional copulas function, which is a flexible statistical tool, could be applied to develop multivariate drought indicators and solve the complicated and nonlinear associations. The aim of this paper is to develop reliable designing, monitoring and prediction indicators for the proper assessment and intervention of drought risk by nature-based solutions (NBS). Using a copula-based multivariate drought indicator (CMDI) that considers all possible variables related to meteorological, agricultural and hydrological droughts is essential for better drought risk assessment and intervention. The CMDI was developed by integrating univariate marginal cumulative distribution functions of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) variables into their joint cumulative distribution function. CMDI was then applied to the selected study catchment (Po Valley, Italy and Spercheios River, Greece) using hydro-meteorological data from gauging stations and ERA5 gridded data for the period 1979-2017.  The result of CMDI showed moderate, severe and extreme drought frequencies in the two selected catchments. The constructed CMDI captured more severe to extreme drought occurrence than the considered single drought indicators. This proved that the CMDI could appropriately represent the complex and interrelated natural variables. The uncertainty analysis based on Monte Carlo experiments confirmed that CMDI is a more robust and reliable approach for assessing, planning and designing a nature-based intervention for drought risk. The findings of this research can provide a reliable way to develop approaches that can be used for assessing and predicting non-linearly related variables or any risk that may occur simultaneously or cumulatively over time.   

Keywords: Drought risk; multidimensional copulas; multivariate indicators, uncertainty analysis; frequency   

Acknowledgements: This work is carried out under the framework of OPERANDUM (OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks) project, which is funded by the Horizon 2020 under the Grant Agreement No: 776848.
Quality of wind characteristics in recent wind atlases over the North Sea
Authors: Kalverla Peter C. , Holtslag Albert A. M. , Ronda Reinder J. , Steeneveld Gert-Jan
Published: March 2020

Many wind energy applications rely on engineering models that simulate the interaction between the wind and the turbine(s). These models often represent the wind in an idealised fashion, which introduces uncertainties that translate into financial risk for investors.

Over the past four years, we investigated these uncertainties by re-evaluating common assumptions about the (offshore) wind field, studying the physics that govern winds in coastal areas, evaluating the representation of offshore winds in weather models, and proposing alternative methods to represent the offshore wind climate in engineering models.

Uncertainties in the wind climate were studied through a number of ‘anomalous wind events’. An important and illustrative example is the low-level jet, which can substantially impact power production and wind loads on the turbine. We found that low-level jets occur often over the North Sea. Moreover, numerical weather prediction models struggle to adequately represent this phenomenon. A climatology based only on observations is also biased, because the observations are limited in time and space. Thus, we combined field observations with output of reanalysis products to obtain a reliable climatology.

At the 2020 general assembly, we will present a new evaluation of three recent wind atlases over the North Sea: ERA5, The New European Wind Atlas (NEWA), and the Dutch Offshore Wind Atals (DOWA). With virtually no bias, DOWA outperforms the other datasets in terms of the mean wind profile and also in the representation of wind shear. The high resolution offered by DOWA (2.5 km) and NEWA (3 km) leads to substantial improvements in the frequency and the level of detail with which low-level jets are captured. However, the timing of the events is a bit off in NEWA. By contrast, DOWA was produced using continuous three-hourly data-assimilation updates, which imposes a much stronger constraint on the simulations. Consequently, the timing of low-level jets in DOWA is much better represented. This makes for a low-level jet climatology with unprecedented accuracy and detail, facilitating resource assessment and future studies on the characteristics of the offshore wind climate.
Evaluating the effect of the 2018 drought on the NEE in the Sorø beech forest by means of trend analysis and mechanistic canopy modelling of GPP.
Authors: Pilegaard Kim , Ibrom Andreas
Published: March 2020

Denmark experienced a severe drought in 2018 lasting from the beginning of May to the end of August with very little rain during this period. The influence of drought on the net ecosystem CO2 exchange (NEE) was analysed at the Danish ICOS DK-Soroe site (a mature beech forest). The site has a very long continuous flux data set starting in June 1996. The annual NEE of the site has been increasing over the years, mainly due to a prolonged growing season in the autumn and CO2 fertilisation (Pilegaard et al., 2011).

The effect of the summer drought in 2018 was analysed by means of linear trend estimation based on monthly trends during 1996-2017. The observed monthly NEE in 2018 was compared to the predicted values from the monthly time series.

The analysis showed an increased NEE in May and June and a strongly reduced NEE in July and August. Overall, the NEE was reduced 25% compared to the predicted value.

The increased NEE in May and June can be explained by the benefit for the photosynthesis of the trees of the increased light and temperature, while there was still a sufficient water content in the soil. By the end of June, the low water content in the soil affected the NEE, and despite some heavy rain in the beginning of August, the NEE only recovered by September.

We used the flux data set together with a mechanistic canopy model to examine the tree physiological nature of the photosynthesis limitation. The results showed that stomatal limitation alone was not able to explain the large reduction of GPP during the drought. Based on these findings, we extended the approach and show the seasonal development of drought induced GPP limitation contrasting stomatal and biochemical photosynthesis limitations.

The effects on NEE and energy partitioning during the 2018 summer drought are compared to previous years with (less severe) summer drought. 

Reference:

Kim Pilegaard, Andreas Ibrom, Michael S. Courtney, Poul Hummelshøj, Niels Otto Jensen. Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009. Agricultural and Forest Meteorology 151 (2011) 934–946.

Acknowledgement:

The study was based on data from ICOS/DK.
Geomechanical characterization of rock masses by means of remote sensing techniques
Authors: Loiotine Lidia , La Salandra Marco , Andriani Gioacchino Francesco , Barracane Giovanni , Derron Marc-Henri , Jaboyedoff Michel , Marsico Antonella , Parise Mario
Published: March 2020

Improving the methods for the characterization of rock masses by integrating traditional field surveys with remote sensing techniques is fundamental for practical and realistic discontinuous modelling, in order to identify the failures and kinematics, develop landslide susceptibility assessment and plan prevention and mitigation measures.

A 20 m-high cliff at Polignano a Mare (Southern Italy) was selected as case study for the presence of well-developed discontinuities (bedding and joints) and due to the local morphology, consisting of a valley with opposite slopes at a distance of 150 m, and a pocket beach at their toe. This configuration allowed to perform both traditional and remote sensing surveys. First, photogrammetry methods were carried out on the ground and with the help of a boat. Structure from Motion (SfM) technique was then used to process and combine the pictures, in order to elaborate a raw point cloud of the case study. Secondly, high resolution Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) techniques were conducted after positioning Ground Control Points (GCPs) all over the rock mass, with the aim of obtaining a more detailed point cloud. Eventually, a unique and optimized georeferenced point cloud was obtained by combining the previous models, also removing the non-geological objects. Furthermore, Infrared Thermography (IT) was carried out in order to investigate the fracture pattern, the areas of concentrated stress, and the presence of humidity and voids.

The structural analysis of the rock mass was performed directly on the point cloud, by testing procedures and algorithms for the automatic identification of discontinuity sets and of their orientation, spacing, persistence and roughness.

The next step of this research will concern the evaluation of the instability mechanisms with the help of kinematic analyses, by means of stereographic projections. Finally, the reliability of the procedure for a complete rock mass characterization, which is expected to be obtained as the final result, will be tested by means of numerical stability solutions, after calibrating the geomechanical model and importing the fracture system in an appropriate software.

 
GNSSpy: Python Toolkit for GNSS Data
Authors: Işık Mustafa Serkan , Özbey Volkan , Bayır Ejder , Yüksel Yiğit , Erol Serdar , Tarı Ergin
Published: March 2020

The use of Python programming language in the academic community increased in recent years. Python is a multi-purpose language and has an easy syntax which makes it appropriate for routine computations. However, there are very few attempts to write GNSS related libraries in Python programming language.

GNSSpy is a free and open-source library for handling multi GNSS and different versions (2.X and 3.X) of RINEX files. It provides Single Point Positioning (SPP) and Precise Point Positioning (PPP) solutions by least squares adjustment using precise ephemeris, differential code biases (DCB) and clock corrections from different solutions. GNSSpy can be used for editing (slicing, decimating, merging) and quality checking (multipath, ionospheric delay, SNR) for RINEX files. It can be successfully used for visualizing GNSS data such as skyplot, azimuth-elevation, time-elevation, ground track, and visibility plot. GNSSpy can be downloaded from GitHub. The toolkit is still being improved by the authors.
Bayesian joint inversion of muographic and gravimetric data for the 3D imaging of volcanoes, case study of the Puy de Dôme
Authors: Barnoud Anne , Cayol Valérie , Lelièvre Peter , Niess Valentin , Cârloganu Cristina , Le Ménédeu Eve
Published: March 2020

We present a method to jointly invert muographic and gravimetric data to infer the 3D density structure of volcanoes.

Muography and gravimetry are two independent methods that are sensitive to the density distribution. The gravimetric inversion allows to reconstruct the 3D density variations but the process is well-known to be ill-posed leading to non unique solutions. Muography provides 2D images of mean densities from the detection of high energy atmospheric muons crossing the volcanic edifice. Several muographic images can be used to reconstruct the 3D density distribution but the number of imagdes is generally limited by instrumentation and field contstraints.

The joint inversion of muographic and gravimetric data aims at reconstructing the 3D density structure of an edifice, benefiting from the advantages of both methods. We developed a robust inversion scheme based on a Bayesian formalism. This approach takes into account the data errors and a priori information on the density distribution with a spatial covariance so that smooth models are obtained. The a priori density standard deviation and the spatial correlation length are the two hyperparameters that tune the regularization, hence that control the inversion result. The optimal set of hyperparameters is determined in a systematic way using Leave One Out (LOO) and Cross Validation Sum of Squares (CVSS) criteria (Barnoud et al., GJI 2019). The method also allows to automatically determine a constant density offset between gravimetry and muography to overcome a potential bias in the measurements (Lelièvre et al., GJI 2019).

The case of the Puy de Dôme volcano (French Massif Central) is studied as proof of principle as high quality data are available for both muography (Le Ménédeu et al., EGU 2016; Cârloganu et al., EGU 2018) and gravimetry (Portal et al., JVGR 2016). We develop and validate the method using synthetic data computed from a model based on the Puy de Dôme topography and acquisition geometry, as well as on real data.
Saltation layer of cohesive drifting snow observed in a wind tunnel
Authors: Ralaiarisoa Jean-Luc Velotiana , Naaim-Bouvet Florence , Kosugi Kenji , Nemoto Masaki , Ito Yoichi , Valance Alexandre , Ould El Moctar Ahmed , Dupont Pascal
Published: March 2020

Aeolian transport of particles occurs in many geophysical contexts such as wind-blown sand or snow drift and is governed by a myriad of physical mechanisms. Most of drifting particle are transported within de saltation layer and has been largely studied for cohesionless particles whether for snow or for sand. Thus, the theoretical description of aeolian transport has been greatly improved for the last decades. In contrast cohesive particles-air system have received much less attention and there remain many important physical issues to be addressed.  

        In the present study, the characteristics of drifting cohesive snow phenomena is investigated experimentally Several wind tunnel experiments were carried out in the Cryopsheric Environment simulator at Shinjo (Sato et al., 2001). Spatial distribution of wind velocity and the mass flux of drifting snow were measured simultaneously by an ultrasonic anemometer and a snow particle counter. The SPC measures the size of each particle passing through a sampling area. The size is classified into 32 classes between 50 and 500µm. Compacted snow was sifted on the floor. Then snow bed is left for a determined duration time to become cohesive by sintering.Two kinds of snow beds with different compression hardness were used (“hard snow” with a compression hardness of about 60 kPa and “semi hard snow” with a compression hardness of about 30 kPa). Wind tunnel velocity varied from 7 m/s to 15 m/s. Moreover steady snow drifting can be produced by seeding snow particles at a constant rate at the upwind of the test section. The results are compared with those obtained for loose surfaces. It was shown that :

- on hard snow cover, aerodynamic entrainment does not occur and saltating particles from the seeder just rebounded without splashing particles composing the snow surface (Kosugi et al.,2004). b, the inverse of the gradient of the mass flux decay with height is proportional to the friction velocity. The mass flux profiles exhibit a focus point. It is also confirmed (Kosugi et al., 2008) that the saltation height increased with increasing particle diameter throughout the full range of investigated wind tunnel velocity. Such characteristics are not observed for cohesionless snow particles (Sugiura et al.,1998)

-on semi hard snow cover, the inter-particle cohesion makes the transport unsteady and spatially inhomogeneous. A steady state is never obtained. It makes experimental protocol and experiments repeatability tricky. Without seeder, the same trends are observed compared to the previous experiments on hard snow. With seeder, the drifting snow flux dramatically increases, even for low wind speed, leading to snow cover vanish.
Proposed best practices for the integration of in situ observations and large scale analysis and forecast systems: case study of the phytoplankton blooming off a Tyrrhenian coastal site
Authors: Salon Stefano , Martellucci Riccardo , Cossarini Gianpiero
Published: March 2020

The coastal systems are among the most dynamic natural systems, being extreme complex zones in which chemical, physical and biological processes interact at different spatial and temporal scales. A holistic approach, based on the integration of multiple monitoring tools for data collection (i.e. satellite imagery, numerical models and in situ observations), may provide different information about coastal ecosystems, at different spatial and temporal scales. Of course, none of these tools is perfect, being each characterized by intrinsic errors and therefore specific uncertainty, the latter also considered as an important subject of investigation.

In this context, our goal is to understand the spatial and temporal distribution of phytoplanktonic biomass in coastal waters in order to evaluate the phytoplankton dynamics in a polluted coastal area located in the northern Tyrrhenian Sea. Long-term high-resolution observations (weekly sampling from 2015 to 2017) of phytoplankton biomass at a coastal site from the C-CEMS observing system (central Tyrrhenian Sea offshore Civitavecchia) are presented, discussed and integrated with the analysis data provided by the Copernicus Marine Environment Monitoring Services (CMEMS) for the Mediterranean Sea, generated by the MedBFM model system, and with satellite observations (from CMEMS Ocean Colour database). The focus of this work is twofold: on one side, to analyse the phytoplankton bloom dynamics of the Civitavecchia coastal ecosystem by adopting a multi-platform approach which integrates CMEMS products and C-CEMS in situ data, on the other side, to propose best practices to integrate multi-platform data streams that may be adopted also in other similar contexts of coastal ecosystems.

The analysis of the time series of phytoplankton provided by in situ, satellite and model data show the typical dynamics of temperate climate, characterized by spring and autumn blooms, together with a significant interannual variability. The EOF analysis has shown consistency among multi-platform datasets. Notwithstanding the incongruences, specifically related to the chlorophyll model outputs, which underestimate the in situ and satellite data and that may be related to some representativeness error (i.e. river nutrient inputs based on climatological information and grid resolution), the intercomparison is beneficial to provide information at different temporal and spatial scales of the phytoplankton dynamics.
Soil-atmosphere CO2 and CH4 fluxes in a nutrient-poor drained peatland forest in boreal Sweden
Authors: Järveoja Järvi , Peichl Matthias , Nilsson Mats B.
Published: March 2020

In countries such as Sweden, where between 1.5 and 2.0 million hectares of natural peatlands have been drained for forestry purposes, knowledge on soil-atmosphere greenhouse gas (GHG) fluxes from these areas is required for national GHG accounting as well as for identifying suitable management strategies (e.g. forestry vs rewetting) to reduce GHG emissions. In this study, we applied the manual chamber method (incl. clear and dark chambers) to investigate the soil-atmosphere carbon dioxide (CO2) and methane (CH4) exchanges in a nutrient-poor drained peatland forest in boreal Sweden over two growing seasons (2018-2019). Combined with an array of vegetated and vegetation-removal plots we further partitioned the soil-atmosphere CO2 exchange into its individual component fluxes of heterotrophic and autotrophic respiration as well as gross and net primary production. In addition, we collected soil environmental, vegetation and meteorological data to determine the key biotic and abiotic controls of these fluxes. All measurements were carried out along multiple transects at 5, 25 and 50 m distances from the main drainage ditch to explore their spatial variability. For comparison, we used similar GHG flux data from an automated chamber system at the nearby natural Degerö mire. We found divergent magnitudes and patterns in the soil-atmosphere CO2 exchange and its component fluxes between the drained peatland forest and the natural mire, altogether resulting in a close-to-zero soil-atmosphere CO2 balance at the drained site compared to a net CO2 uptake at the mire. The CH4 emissions from the drained peatland forest were significantly reduced compared to the natural mire; however, due to a relatively high mean water table level the drained site continued to act as a persistent CH4 source. Overall, these detailed data will serve as a baseline for evaluating the impact of future rewetting activities (planned for 2020 at the site) on the GHG balance and will provide the various forest stakeholders valuable decision-support for developing sustainable and climate-responsible forest management strategies.
Surface ozone and land-atmosphere coupling
Authors: Emmerichs Tamara , Ouwersloot Huug , Kerkweg Astrid , Fares Silvano , Mammarella Ivan , Taraborrelli Domenico
Published: March 2020

Surface ozone is a harmful air pollutant, heavily influenced by chemical production and loss processes. Dry deposition to vegetation is a relevant loss process responsible for 20 % of the total tropospheric ozone loss. Its parametrization in atmospheric chemistry models represents a major source of uncertainty for the global tropospheric ozone budget and might account for the mismatch with observations. The model used in this study, the Modular Earth Submodel System (MESSy2) linked to ECHAM5 as atmospheric circulation model (EMAC) is no exception. Like many global models, EMAC employs a “resistances in series” scheme with the major surface deposition via plant stomata which is hardly sensitive to meteorology depending only on solar radiation. Unlike many global models, however, EMAC uses a simplified high resistance for non-stomatal deposition which makes this pathway negligible.                             

Hence, a revision of the dry deposition scheme of EMAC is desirable. The scheme has been extended with empirical adjustment factors to predict stomatal responses to temperature and vapour pressure deficit. Furthermore, an explicit formulation of humidity depending non-stomatal deposition at the leaf surface (cuticle) has been implemented based on established schemes. Next, the soil moisture availability function for plants has been critically reviewed and modified in order to avoid a stomatal closure where the model shows a strong soil dry bias, e.g. Amazon basin in dry season.

The last part of the presentation will show comparisons of dry deposition velocities and fluxes comparing simulations with data obtained from four experimental sites where ozone deposition is measured with micrometeorological techniques. The impacts of the changes on daily and seasonal patterns of ozone dry deposition will be discussed with a highlight on surface ozone, global distribution and budget.
Ice-nucleating properties of Icelandic dust in mixed-phase cloud conditions
Authors: Umo Nsikanabasi , Schuapp Caroline , Waldhauserová Pavla Dagsson , Weidler Peter G. , Höhler Kristina , Arnalds Olafur , Möhler Ottmar
Published: March 2020

The emission of natural dust particles into the atmosphere from the high-latitude/cold regions is fast-becoming more important than previously thought. Due to land use and climate changes, a vast expanse of land surface previously covered by ice is getting exposed; hence, leading to an increase in dust emissions from these regions. Currently, an estimated 500,000 km2 land surface area is contributing up to 100 Tg of dust annually1. Aside from the direct impact of this dust on the air quality and direct solar radiation budget, it can also influence the cloud glaciation processes. Many studies have clearly established that mineral dust aerosol particles are generally good ice-nucleating particles2. However, most of these ice nucleation studies have been conducted on dust from deserts and mid-latitude regions. At present, our understanding of the ice-nucleating abilities of dust from high-latitude regions is highly limited. Here, we report the first comprehensive quantification of ice-nucleating properties of dust obtained from a typical high-latitude region – Iceland. We engaged two laboratory set-ups for this investigation – the Aerosol Interactions and Dynamics in the Atmosphere (AIDA) cloud simulation chamber, and the Ice Nucleation Spectrum of Karlsruhe Institute of Technology (INSEKT). Based on the INAS density calculations which we adopted in quantifying the Icelandic dust ice-nucleating efficiencies, our current results show that dust from Iceland nucleates ice effectively in the range of ~ 103 – 1012 m-2 in the temperature range studied (266 K - 238 K). A preliminary assessment shows that from ~ 250 K its ice-nucleating abilities can compete with that of desert dust and agricultural soil dust. Currently, work is ongoing to understand the role that mineral composition plays in ice nucleation behaviour. Potentially, our new results suggest that the high-latitude dust source could contribute to the INP budget of clouds in the region and may influence precipitation and the climate conditions in high-latitude regions.

Bullard, J. E. et al. High-latitude dust in the Earth system. Reviews of Geophysics 54, 447–485 (2016).

Hoose, C. & Möhler, O. Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments. Atmos. Chem. Phys. 12, 9817–9854 (2012).
Do local kinematics have an effect on the recrystallized grain size piezometer?
Authors: Kilian Rüdiger , Stipp Michael
Published: March 2020

The quartz recrystallized grain size piezometer was determined by axial shortening experiments on Black Hills quartzite in Griggs type triaxial deformation apparatus (Stipp & Tullis, 2003). The analysis of general shear experiments on Black Hills quartzite (Heilbronner & Kilian, 2017) reveal a striking discrepancy between both experimental  setups; at a given differential stress, recrystallized grains are much larger in the general shear experiments than in axial shortening.
A major difference between both sets of experiments is, that the finite grain volume of quartz in the general shear experiments almost entirely consists of recrystallized grains while the here investigated axial shortening experiments have fractions of recrystallized grains in the range of 15 to 30% in the high stress experiments and up to 60% in the low stress experiments. Quartz in the general shear experiments developed a moderate to strong crystallographic preferred orientation (CPO) while, apart from a Dauphiné-induced ordering of poles to {10-11} and {01-11}, no overall significant CPO developed in the axial shortening experiments.
Based on the analysis of the EBSD data of Cross et al. (2017), we observed that the dispersion axes of large quartz grains in the axial shortening experiments correspond to the global kinematic reference frame. The dispersion axes of the fraction of small, recrystallized grains depend on the local kinematics between the porphyroclasts. Slip transparency indicates that boundaries between the largest grains are rather hard while recrystallized grains can accommodate strain induced by crystal plastic slip more effectively and homogeneously.
These results suggest that recrystallized grains in the axial shortening experiments, at least in those with low fractions of recrystallized grains, correspond to a material deforming at a rate higher than the imposed shortening rate while the axial load is predominantly supported by the porphyroclasts. In contrast, recrystallized grains in general shear experiments deform at the imposed (global) rate and derived stresses correspond on average to the deforming zone. Due to strain and strain rate inhomogeneities in the latter experiments, however, there is a systematic variation in recrystallized grain size across the general shear zone. We compare these local microstructural variations and discuss their significance for the recrystallized grain size piezometer calibration.
Linking the mechanics of polygonal faults with hydrothermal activity and marine biosphere – the Guadeloupe geothermal system
Authors: von Hagke Christoph , Leu Katharina , Luijendijk Elco , Philippon Melody , Back Stefan , Lebrun Jean-Frederic , Cordonnier Sebastien , Gros Olivier , Gonzalez-Rizzo Silvina , Gay Aurelien
Published: March 2020

Polygonal faults are ubiquitous features, commonly observed in seismic images of fine-grained sedimentary successions along many passive margins. They are characterized by covering large parts of the basin with a typical polygonal pattern. In the last decade, different mechanical models for the generation of polygonal faults have been proposed; however, as they are commonly formed at depth and not directly observable at the surface, their formation remains a matter of debate. As part of the GEOTREF Program (ADEME – Investissement d’avenir) we found polygonal fault structures exposed close to the surface in marine soft sediments at 5 m water depth at the western coast of Guadeloupe. The structures are associated with fault-bound thermal springs and clearly visible at the sea bottom due to preferential precipitation of sulfur minerals and concentration of diatoms. In a multidisciplinary study involving a team of hydrogeologists, marine micro-biologists, and structural geologists, we study the genesis of polygonal faults in this setting. We analyzed the sediments in which the polygonal faults formed structurally and geochemically. First results suggest that SiO2 precipitated from hydrothermal fluids increases the cohesion of the most permeable soft sediments. Dewatering of the underlying layers causes the formation of polygonal faults at a depth of <1 m. These polygonal faults then act as channels for hot fluids, resulting in accumulation of sulfur favoring the establishment of diatoms at the surface. This study offers the unique opportunity to study the formation of polygonal faults in situ. We compare the observed geometries of polygonal faults with GEOTREF cruise 2-D seismic data offshore Guadeloupe, and 3-D seismic data of polygonal faults in New Zealand and Australia with the goal to understand the variability of polygonal fault geometries, as well as their comparability across different scales of observation. On a more local scale, this study provides insights how fracture dynamics guides fluid flow, which in turn interacts with the marine biosphere.
Accuracy and reproducibility of the triple oxygen isotope measurement of silicate micro-samples by laser-fluorination-IRMS
Authors: Couapel Martine , Sonzogni Corinne , Alexandre Anne , Sylvestre Florence
Published: March 2020

Recent studies showed that the 17O-excess of plant leaf biogenic silicates (phytoliths) can be used to quantify the atmospheric relative humidity occurring during leaf water transpiration. The 17O-excess vs ∂18O signature of phytoliths can also be used to trace back to the signature of leaf water. In a similar way, the signature of lacustrine diatoms is expected to record the signature of the lake water in which they formed. Therefore, the triple oxygen isotope composition of biogenic silicates extracted from well-dated sedimentary cores may bring new insights for past climate and hydrological reconstructions. However, for high time-resolution reconstructions, we need to be able to measure microsamples (300 to 800 µg) of biogenic silica. In another context, the triple oxygen isotope composition of micro-meteorites constitutes an efficient tool to determine their parent-body. In this case too, micro-samples need to be handled.

Here we report the results of new ∂18O and ∂17O measurements of macro- and micro-samples of international and laboratory silicate standards (e.g. NBS28 quartz, San Carlos Olivine, Boulangé quartz, MSG phytoliths and PS diatoms). Molecular O2 is extracted from silica and purified in a laser-fluorination line, passed through a 114°C slush to condense potential interfering gasses and sent to the dual-inlet Isotope Ratio Mass Spectrometer (IRMS) Thermo-Scientific Delta V. In order to get sufficient 34/32 and 33/32 signals for microsamples the O2 gas is concentrated within the IRMS in an additional auto-cooled 800 ml microvolume tube filled with silica gel. Accuracy and reproducibility of the ∂18O, ∂17O and 17O excess measurements are assessed. Attention is payed to determine the concentration from which O2 gas yields offsets in ∂18O, ∂17O and 17O-excess are measured and whether these offsets are reproducible and can be corrected for.
Developing an operational high-resolution hydrometeorological system in a Mediterranean region: predictability analysis of two case studies
Authors: Furnari Luca , Senatore Alfonso , Magnusson Linus , Mendicino Giuseppe
Published: March 2020

Given the expected increase in the frequency and intensity of severe weather events due to global warming, improving weather forecasting capability in terms of both spatial resolution and lead times is a key factor for reducing extreme events impact. The climate of the Calabrian peninsula (southern Italy) is dominated by the interactions of the air masses with the surrounding Mediterranean Sea and strongly influenced by its complex steep orography, which often amplifies precipitation amounts worsening ground effects.

With the aim of investigating the capability of a state-of-the-art modelling chain to deliver accurate forecasts for civil protection purposes in the Calabria Region, an experimental high-resolution hydrometeorological modelling system has been developed recently at the Department of Environmental Engineering of the University of Calabria, providing forecasts up to the hydrological impact. The system is based on the Advanced Research WRF (ARW) mesoscale model in its version 3.9.1, with two one-way nested domains, the innermost having 2-km resolution. The boundary and initial conditions are provided operationally by the Global Forecasting System (GFS) in its high-resolution version and, for back-analysis purposes, by the European Centre for Medium-range Weather Forecasts’ Integrated Forecasting System (IFS). Finally, to simulate the hydrological impact of the atmospheric forcing, the WRF-Hydro 5.0 modelling system in a one-way mode with a horizontal resolution of 200 m is linked to the system and applied on all the main river networks of the region.

The accuracy and efficiency of the system have been tested with two events occurred in Autumn 2019. Though the synoptic conditions showed some significant differences, both the events affected mainly the central part of the region, causing about 230 mm and 200 mm of rainfall in 72 hours, on the 11-13 November 2019 and on the 24-26 November 2019, respectively. The analysis focused particularly on the predictability of the events, evaluating the forecast accuracy by considering lead times from one week early.

Preliminary results highlight the ability to forecasts the events well in advance, proved by the comparison of the simulated rainfall with the ground-based observations and the reproduction of the main hydrological signals in the basins affected by the events.
Impact of interactive sea surface temperature on convective clustering in radiative convective equilibrium
Authors: Semie Addisu Gezahegn , Tompkins Adrian Mark
Published: March 2020

We present results of radiative convective equilibrium runs using the WRF model coupled to an interactive slab ocean model, for which a relaxation term removes energy to constrain the domain mean sea surface temperature to a target value over a given timescale. By using a short adjustment timescale of one minute, drift in the mean temperature is constrained and the impact of the slab ocean is only through the spatial heterogeneity in sea  surface flux. We show how thin slabs slow the onset of organization, and conduct sensitivity experiments to determine the relative contributions of the radiative, sensible and latent surface fluxes, with surface fluxes key. Once clustering starts, the surface feedback acts to aid organization onset due to the drying atmosphere, although the speed of clustering onset is not significantly changed, indicating that it could be determined by a water vapour diffusive timescale as suggested by Windmiller and Craig.  An additional set of experiments that permit the mean surface temperature to undergo a diurnal adjustment show how diurnal variations in SST oppose the atmospheric radiative forcing and also act to prevent clustering onset. We show the mechanism for this acts through the reduction of the diurnal variation of convective mass flux and the distance between updraft towers.
Intervening in interventions: Exploring the implications of novel technologies through multidisciplinary lenses.
Authors: Redeker Kelly , Brown Eleanor , Brooks Sally , Dunlop Lynda , Kirshner Joshua , Friend Richard , Walton Paul
Published: March 2020

We present a British Academy funded Knowledge Frontiers project which brought together an interdisciplinary  team of social (Anthropology, Education, Human Geography, Politics) and scientific (Biology, Chemistry, Environmental Science) researchers to explore the implications of bioethanol-from-cellulose reactors, a novel technology that may provide an innovative, partial solution to the global need for sustainable fuels. These reactors utilize ‘waste’ biomass, either residue from crops or that which can be grown on ‘marginal lands’, thus producing (second generation) biofuels while avoiding the “food versus fuel” debate. The team analysed assumptions inherent within this approach and considered how to interact with this innovation/implementation process to maximally address broader social and environmental goals. 

As a research community we queried the priorities and criteria used in developing new technological solutions and investigated how decisions were made across a range of stakeholders. We focused specifically on a case study of the first large-scale second generation bio-refinery, located in Brazil. Developing ongoing and consistent relationships between social scientists and natural scientists were key to delivering project aims, including documentation of the processes of learning/interacting that we engaged in as a team and ongoing dialogues across research assumptions and expectations within different disciplines. 

Key components of the interdisciplinary process that appeared to be necessary for success included i) providing sustained and open opportunities for interaction between researchers to develop effective communication across disciplines, ii) explicitly exploring discipline-specific taken-for-granted assumptions and identifying what individuals understand when talking about key terms and processes (in this case these included, for example, ‘sustainable’, ‘development’, ‘methodology’, ‘marginal land’ and ‘research outputs’), iii) creating solidarity within the research community, which is critical for effective interaction between disciplines and cultures. This interplay between disciplines provides an innovative way to influence decision-making in science directly, especially at early stages of development. By directly addressing these requirements, multi/transdisciplinary challenges can be addressed in a manner which is more open, more critical and more able to reveal most effective solutions.