bluuebunny/crossref_metadata_2025 huggingface dataset:
Big Earth Data enhance the Implementation of PEEX along the Belt and Road regions
Authors: Qiu Yubao , Guo Huadong , Liu Jie , Chen Fang , Menenti Massimo
Published: March 2020

The Digital Belt and Road program, the DBAR, is aiming to resolve the scientific understanding of the Earth changes, and sustainable development goals along the Belt and Road regions (B&R), which was initiated in 2016, and now have been developing into its 1st phase of implementation plan after the startup phase. With a strong collaboration and common interest, the Pan-Eurasia experiment the PEEX, and DBAR is crossed together to use the Earth observations to understanding and address the challenges for the environmental changes, especially for the Belt and Road in Asia about the changing of snow and ice, vegetation and ecosystem, disaster, urban, agriculture, water stress and etc.

With the development of the Earth Observations, either from the ground observations or the space/air borne platform, the Big Earth Data approach has been developing for addressing the societal and science challenges for the PEEX and DBAR common domain, with the eight working group efforts, and its potential contribution to the working efforts for the PEEX. In this talk, we will describe the Big Earth Data, societal challenges, its platform development, and more focus will be put in the snow and ice, urban, environment, disaster, and water as the priorities for the cross feralization with PEEX.
Aeolus aerosol and cloud product
Authors: Dabas Alain , Flament Thomas , Trapon Dimitri , Huber Dorit
Published: March 2020

Aeolus is a high-spectral resolution UV lidar. It implements two detection channels, a broadband (Rayleigh channel) and a narrowband (Mie channel). Carefully calibrated, the combination offers the possibility to derive independent estimates of the backscatter and extinction coefficients of the clouds and the aerosols, thus opening the possibility to acquire an information on their nature with the extinction-to-backscatter ratio. The presentation will show how the level-2A processor of the mission works for the retrieval of optical properties of cloud and aerosol particles, what products can be obtained with what limitations. The potential of L2A processor will be illustrated by results obtained on real data acquired since AEOLUS launch.
Is there a 'right' spatial scale? Improving pedological multi- scale modelling by optimizing input data grain size: A Case Study using Average Local Variance.
Authors: Scarpone Christopher , Knudby Anders , Melles Stephanie , Millward Andrew
Published: March 2020

Current soil mapping practitioners are faced with a plethora of choices of digital data for input to their modelling approaches; these data have local to global extents and are highly variable in their grain size. Deciding at what scale to represent individual covariates for a specific project, therefore, can be difficult and confusing. Moreover, a lack of accessible methodology and tools focused on determining an optimal input data scales (grain size) has led to the current status quo, which is to use data at the scale delivered by the data provider. Soil prediction models are typically applied using the grain size of the coarsest variable, scaling other data to match. In this study, average local variance was investigated as a method to determine optimal grain size(s) for input variables to a soil contaminant prediction model. The Meuse dataset was used, and heavy metal soil contamination was mapped using RandomForest. A Data Cube was employed to handle data inputs of varying grain size. Two scenarios were investigated for model prediction accuracy: (1) contaminant predictions made using data with optimized grain size, and (2) contaminant predictions made using input data where grain size was unchanged, “as received” from the data provider. Both model predictions were assessed using a cross-validation approach. Early results indicate that optimization of grain size based on average local variance can improve prediction accuracy and point toward the importance of understanding the spatial heterogeneity of an input variable and how it changes with different grain sizes prior to incorporation in a predictive model. This research lays a foundation for the creation of an automated approach practitioners can use to help untangle the relationship between the intrinsic spatial scale for a process of interest and how that process is represented in the scale of input data.
Crust and upper mantle structure of the Ligurian Sea revealed by ambient noise tomography using ocean bottom seismometer data
Authors: Wolf Felix Noah , Lange Dietrich , Kopp Heidrun , Dannowski Anke , Grevemeyer Ingo , Crawford Wayne , Froitzheim Nikolaus , Thorwart Martin , Paul Anne ,   AlpArray Working Group
Published: March 2020

The Liguro-Provencal-basin was formed as a back-arc basin of the retreating Calabrian-Apennines subduction zone during the Oligocene and Miocene. The resulting rotation of the Corsica-Sardinia block at roughly 32–24 Ma is associated with rifting, shaping the Ligurian Sea. It is highly debated though, whether oceanic or atypical oceanic crust was formed or if the crust is continental and experienced extreme thinning during the opening of the basin.

To investigate the velocity structure of the Ligurian Sea a network (LOBSTER) of 29 broadband Ocean Bottom Seismometer (OBS) was installed jointly by GEOMAR (Germany) and ISTerre (France). The LOBSTER array measured continuously for eight months between June 2017 and February 2018 and is part of the AlpArray seismic network. AlpArray is a European initiative to further reveal the geophysical and geological properties of the greater Alpine area.

We contribute to the debate by surveying the type of crust and lithosphere flooring the Ligurian Sea.
Because of additional noise sources in the ocean, causing instrument tilt or seafloor compliance, OBS data are rarely used for ambient noise studies. However, we extensively pre-process the data to improve the signal-to-noise ratio. Then, we calculate daily cross-correlation functions for the LOBSTER array and surrounding land stations. Additionally, we correlate short time windows that include strong events. The cross-correlations of these are dominated by earthquake signals and allow us to derive surface wave group velocities for longer periods than using ambient noise only. Finally, phase velocity maps are obtained by inverting Green’s functions derived from cross-correlation of ambient noise and teleseismic events, respectively. The phase velocity maps show strong heterogeneities for short periods (5-15 s, corresponding to shallow depths). Causes for these include varying sediment thickness, fault zones and magmatism. For longer periods (20-80 s) the velocity structure smoothens and reveals mantle velocities north-northwest of the basin centre. This might hint on an asymmetric opening of the basin. We do not see strong indications for an oceanic spreading centre in the Ligurian basin.
Thermochemical structure of cratons from Rayleigh wave phase velocities
Authors: Goes Saskia , Eeken Thomas , Altoe Isabella , Petrescu Laura , Foster Anna , Pedersen Helle , Arndt Nick , Darbyshire Fiona , Bouilhol Pierre
Published: March 2020

The thermal and compositional structure of the lithospheric keels underlying the Precambrian cratonic cores of the continents may shed light on their evolution and long-term stability. A number of seismic studies have found significant 3D seismic heterogeneity in cratonic lithosphere, which is enigmatic because temperature variations in old shields are expected to be small and seismic sensitivity to major-element compositional variations is limited. Previous studies show that metasomatic alteration may lead to significant variations in shield velocities with depth. Here we perform a grid search for thermo-chemical structures including metasomatic compositions, to model Rayleigh-wave phase velocities between 20 and 160 s for the northeastern part of North America comprising the Superior craton, the largest Archean craton in the world, and surrounding Proterozoic belts. We find smooth variations in thermal structure that include variations in thermal thickness within the Superior and decreasing thickness towards the edges of the shield. Four types of distinct compositional structures are required to match the long-period phase velocities. The different types appear to correlate with: (i) the unaltered oldest cores of the Superior, (ii) Archean and Proterozoic lithosphere modified by rifting and plume activity, and two distinct types of subduction signatures: (iii) an Archean/Paleo-Proterozoic signature that includes a high-velocity eclogite layer in the mid-lithosphere and (iv) a post Paleo-Proterozoic signature characterised by strongly altered shallow mantle lithosphere. Thus, processes that have affected the formation and modification of cratonic lithosphere and were previously recognised in xenoliths appear to have also left large-scale imprints in seismic structure.
An empirical cross sensor model for high-resolution multispectral imagery
Authors: Vellalapalayam Subramanian Manivasagam , Kaplan Gregoriy , Rozenstein Offer
Published: March 2020

The availability of public-domain high-resolution satellite imagery such as Sentinel-2 and Landsat-8 has increased earth observation (EO) studies across the globe. Empirically combining different EO sensor data into a single dataset increases the temporal coverage, which is useful for land-cover monitoring. In this study, a transformation model was developed for Sentinel-2 and Vegetation and Environmental New micro Spacecraft (VENμS) imagery over Israel. Both sensors offer high spatio-temporal resolution imagery, i.e., VENμS has a 10m spatial resolution with a two-day revisit period, and Sentinel-2 has a 10-20 m spatial resolution with a five-day revisit period. Near-simultaneously acquired imagery was employed for the transformation model development. The model coefficients were derived for the overlapping spectral regions of both sensors. Further, the transformation model performance was tested using various statistical measures, namely, orthogonal distance regression (ODR), spectral angle mapper (SAM), and mean absolute difference (MAD). The validation results highlighted that MAD values were reduced between Sentinel-2 and transformed VENμS reflectance. Similarly, the ODR slope values became closer to one, and the overall spectral similarity increased as demonstrated by a decrease in SAM values. This transformation function creates a unified reflectance dataset in the form of a dense time-series of observation, especially useful for vegetation monitoring.
Influence of crop-water production functions on the performance of economic instruments for water conservation
Authors: Sapino Francesco , Pérez-Blanco Carlos Dionisio , Gutiérrez-Martín Carlos , Pulido-Velazquez Manuel , García-Prats Alberto
Published: March 2020

In water scarce basins, the agricultural economics modeling literature predicts water demand and supply curves with significant inelastic intervals, which limit the cost-effectiveness of charges and water reacquisitions in reallocating water to the environment, respectively. Such models typically rely on yield point predictions that are obtained as an average of past observations, while water input application per crop is assumed constant on a per hectare basis. Yield point predictions allow modeling irrigator’s adaptation at the extensive (land reallocation towards less water-intensive crops) and super-extensive margins (land reallocation towards rainfed crops); yet, they are not suitable for modeling adaptation at the intensive margin, which involves decremental water input application through deficit irrigation -an increasingly frequent response to water scarcity in arid and semi-arid basins. This paper introduces agronomic calibrated production functions into a multi-attribute positive calibrated model to simulate adaptation at the intensive, extensive and super-extensive margins. The model is illustrated with an application to the El-Salobral-Los Llanos irrigated area in the Mancha Oriental (Spain). Agronomic production functions are calibrated for the main crops in the area, namely wheat, barley, corn, alfalfa and onion, which represent 78% of agricultural land use. Results for a hypothetical policy that increases charges from 0 to 100 Eurocents/m3 suggests a relevant role for intensive margin adaptation in the case of cereal crops; while farmers prefer to fully irrigate more profitable horticultural crops (onion). As a result, introducing adaptation at the intensive margin results in a significantly more elastic water demand curve. For example, at a charge increase of 20 Eurocents/m3, the model using agronomic production functions predicts a water conservation of 3855 m3/ha; as compared to 3123 m3/ha in the model relying on yield point predictions (a non-negligible difference of 18.97%).
Sorption and Degradation of Selected Pharmaceuticals in Controlled Laboratory Column Experiments
Authors: Schübl Marleen , Kiecak Aleksandra , Stumpp Christine
Published: March 2020

Pharmaceutically active compounds have increasingly been detected in groundwater worldwide. Despite constituting a major risk for ecosystems and human health, their fate in the environment has still not been thoroughly investigated. This study characterizes the transport behavior of five selected pharmaceutically active compounds (antipyrine, atenolol, caffeine, carbamazepine and sulfamethoxazole) in two sediments (coarse quartzsand and sandy loam) using column experiments with long-term injection of spiked groundwater accompanied by monitoring of microbial activity in the columns. Transport parameters were estimated using an analytical reactive transport model. When five selected compounds were injected simultaneously, transport behavior of antipyrine, carbamazepine and the antibiotic sulfamethoxazole were similar to the conservative tracer in both sediments and under varying redox conditions. During the entire duration of the experiments of about two months no degradation was observed, thus showing the low potential for natural attenuation. Atenolol and caffeine were subject to retardation which was significantly stronger in the sandy loam sediment compared to the coarse quartzsand. This was attributed to higher contents in clay and organic carbon in sandy loam. Biodegradation of caffeine was observed in three out of four non-sterilized settings after an adaption period of 120 to 420 hours and was dependent on the presence of dissolved oxygen. Atenolol was biologically degraded in the coarse quartzsand while the type of degradation remained unclear in the sandy loam sediment. The identification of biodegradation processes was supported by monitoring of intracellular adenosine triphosphate (ATPitc) as a measure for microbial activity. ATPitc was present in varying concentrations in all sediments with higher concentrations when degradation of pharmaceuticals, especially caffeine, was observed. When only caffeine and sulfamethoxazole were injected simultaneously, sulfamethoxazole was degraded while caffeine was not. The latter seems to be influenced by low concentrations in dissolved oxygen rather than the presence of the antibiotic sulfamethoxazole. Results of these experiments emphasize the impact of sediment type and redox conditions on pharmaceutical transport as well as the effect of combination and variety of pharmaceuticals that are released together into the environment.
Modelling and mapping soil pH in Andalusia (Spain) using phenological products as predictor features
Authors: Canero Francisco M. , Rodriguez-Galiano Victor , Cardenas-Martinez Aaron , Luque-Espinar Juan Antonio
Published: March 2020

Soil pH is one of the most important soil parameters, due to its importance for for soil management and food security. Spatial distribution of pH could altered by the different environmental conditions, such as geology, climate or soil-vegetation interactions. pH has an ecological function in controlling spatial distribution of plant species, conditioning absence or presence of different species due to soil pH ability or modifying mineral solubility. Hence, pH and remotely sensed land surface phenology (LSP) could be associated. The objective of this work was two-folded: i) mapping the soil pH of Andalusian soils and ii) the evaluation of new features derived from remote sensing which are related to seasonal cycles of vegetation applied to digital soil mapping

We developed a pH model using 3215 pH measurements at different locations together with three types of predictor features: terrain (elevation, slope, hydrological attributes…), climatic (annual and monthly precipitation and maximum and minimum temperatures) and phenological features extracted from remotely sensed vegetation indices time series (date of the start of spring, date of the end of senescence, growing season length, end of the growing season, length of the growing season, maximum peak, and large seasonal integral as a proxy of productivity). The LSP features were obtained from time series of NDVI that were computed from the MODIS weekly surface reflectance product (MOD09Q1 v6) at a spatial resolution of 250 for the entire study period. The performance of  multiple lineal regression (MLR) and Random Forest was evaluated within the framework of a high dimensional feature space.

The results showed that RF outperformed MLR (R2: 0.66 and 0.58; RMSE: 0.76 and 0.83). ph and feature pairwise correlations were higher for the phenological features: median of large integral (-0.55); median of maximum peak (-0.51); valley depth (0.48); median of date of start of spring (-0.47), median of value on the date of start of spring (-0.46). The most important features in RF prediction were almost the same: the median of large integral, valley depth, maximum temperatures in September and median of maximum peak, showing that LSP features were relevant in pH spatial modelling, with an better performance of RF model.
A phase field method pore-scale model for simulating kinetic interface sensitive tracers reactive transport in porous media two-phase flow systems
Authors: Gao Huhao , Tatomir Alexandru , Karadimitriou Nikolaos , Sauter Martin
Published: March 2020

Over the last few years, our understanding of the processes involved in the application of Kinetic Interfacial Sensitive (KIS) tracers in two-phase flow as a means to quantify the fluid-fluid interfacial area has been enhanced with the use of controlled column experiments (Tatomir et al. 2015,2018). However, there are still some open questions regarding the effect of immobile water, either as capillary and dead-end trapped water or as a film, and the measured by product concentration at the outflow.

In this study, a new pore-scale reactive transport model is presented, based on the phase-field method, which is able to deal with the KIS tracer interfacial reaction and selective distribution of the by-production into the water phase. The model is validated by comparing the analytical solutions for a diffusion process across the interface and a reaction-diffusion process, and is tested for a drainage process in a capillary tube for different Péclet numbers. The applicability of the model is demonstrated in a realistic 2D porous medium NAPL/water drainage scenario used in the literature. Four case studies are investigated in detail to obtain macroscopic parameters, like saturation, capillary pressure, specific interfacial area, and concentration, for a number of combinations between the inflow rate, the contact angle and diffusivity. We derive a relation between the by-product mass at the outflow and the mobile part of the interfacial area, which is formulated by adding a residual factor. This term relates to the part of the by-product produced by mobile interface that becomes residual in the immobile zones.
Sea Ice in the Greenland Polynya in 2018 - A Study with CryoSat-2 and SMOS
Authors: Zhu Weixin , Zhou Lu , Xu Shiming
Published: March 2020

Abstract

Arctic sea ice is a critical component in the global climate system. It affects the climate system by radiating incident heat back into space and regulating ocean-atmosphere heat and momentum. Satellite altimetry such as CryoSat-2 serves as the primary approach for observing sea ice thickness. Nevertheless, the thickness retrieval with CryoSat-2 mainly depends on the height of the ice surface above the sea level, which leads to significant uncertainties over thin ice regimes. The sea ice at the north of Greenland is considered one of the oldest and thickest in the Arctic. However, during late February - early March 2018, a polynya formed north to Greenland due to extra strong southern winds. We focus on the retrieval of sea ice thickness and snow conditions with CryoSat-2 and SMOS during the formation of the polynya. Specifically, we investigate the uncertainty of CryoSat-2 and carry out inter- comparison of sea ice thickness retrieval with SMOS and CryoSat-2/SMOS synergy. Besides, further discussion of retrieval with CryoSat-2 is provided for such scenarios where the mélange of thick ice and newly formed thin ice is present.
Transient Buried Landscapes as Manifestations of Icelandic Plume Activity
Authors: Conway-Jones Benedict , White Nicky
Published: March 2020

We present a suite of four ancient buried landscapes that occur beneath the southeastern flank of the Faroe-Shetland basin on the fringes of the North Atlantic Ocean. These landscapes have been mapped on a calibrated three-dimensional seismic reflection survey. They are manifest as regional unconformities, representing repeated transient sub-aerial exposure events during Early Paleogene times. Once flattened, decompacted and depth converted, these landscapes equate to minimum transient uplifts of O(200)m.  Buried ephemeral landscapes are excellent natural experiments that develop over geological time on large spatial scales with known lithologies, exposure times and initial topographies. Dendritic drainage patterns recovered from these landscapes are highly disequilibrated and contain multiple knickpoints that are systematically arranged within catchment areas. Applying the stream power law, longitudinal rivers profiles are inverted to calculate spatially and temporally varying uplift histories. These unique landscapes are attributed to laterally advecting pulses of hot material that travel away from the Icelandic plume. They provide valuable insights into the dynamics of flow within an asthenospheric channel associated with a mantle plume. Diachronous V-shaped ridges straddling the Reykjanes Ridge independently record advecting thermal pulses of the Icelandic plume. We combine histories of vertical motions with a compilation of independent observations, including V-shaped ridges, to present a semi-continuous thermal history of Icelandic plume pulses.
Determining the range for CMIP climate projections for Europe using a sub-selected model ensemble based on key model performance indicators and key regional physical processes.
Authors: Palmer Tamzin , Mc Sweeney Carol , Booth Ben
Published: March 2020

An alternative approach to constraining climate projections based on a probabilistic approach with observational constraints, is to select a subset of models from the ensemble based on their ability to represent key physical processes, along with some indicators of model performance. The method that is presented here is based on the assumption that if a model is unable to reproduce the key factors important for determining the regional climate, the projections from this model are not considered reliable. The projection range for CMIP5 for the three EUCP European regions is assessed using two different subsampled model ensembles.

The first sub-sampling method presented uses the approach of Mc Sweeney et al. (2015), which assessed the models based on their performance for the UK climate. Each model in the CMIP5 ensemble (where data is available), is firstly assessed against these key performance indicators and poor performers eliminated from the selection. Several models also share large portions of code and therefore have similar errors and projections, Sanderson et al 2015a and 2015b quantifies these similarities. This analysis was used identify ‘near-neighbours’ and further reduce the selection. The applicability of a sub-selection of models based on their performance for the UK climate is assessed for the wider European area and found to reduce the projected range for the Northern European Area (NEU), for precipitation and near surface temperature considerably. The impact on the projected ranges for the Central European Area (CEU) and the Mediterranean (MED) was not as large, suggesting that a different set of physical processes are of primary importance for these regions.

To further investigate the effect of subsampling based on physical processes, a subset of CMIP5 models identified by the approach of Vogel et al. (2018) has been applied for the EUCP European areas. Vogel et al. (2018) looked at the ability of the CMIP5 models to reproduce the correlation between the hottest day of the year and precipitation within the same range as that found in the observations. This approach is designed to subsample the ensemble based on the ability of the model to represent soil moisture feedback processes with the atmosphere. It is thought that these processes are likely to be increasingly important for determining the projected climate in the CEU and MED regions.  

Finally, the projection range for the CMIP6 ensemble in the EUCP regions for precipitation and the near surface temperature will be presented and compared with those for CMIP5.
The impact of the 2019 Ridgecrest earthquake sequence on time-dependent earthquake probabilities for the Garlock fault, California, USA
Authors: Carena Sara , Verdecchia Alessandro , Valentini Alessandro , Pace Bruno
Published: March 2020

The 2019 M 6.4 Searles Valley and the M 7.1 Ridgecrest earthquakes occurred in the Eastern California Shear Zone (ECSZ) between the southern tip of the Owens Valley fault and the central segment of the Garlock fault. This earthquake sequence, as shown by recent studies based on cumulative (coseismic plus postseismic) Coulomb stress (ΔCFS) modeling, is likely to have been influenced by previous earthquakes in the ECSZ, reinforcing the hypothesis that the spatial and temporal distribution of major earthquakes in this region is controlled by the location and timing of past events. In turn, the 2019 Ridgecrest sequence has likely reshaped the state of stress on neighbouring faults, and as a consequence modified the probability of occurrence of future events in the region.

Here, focusing on the Garlock fault, we calculate the cumulative ΔCFS due to several major (M ≥ 7) earthquakes which occurred in the ECSZ and surrounding areas (e.g. San Andreas fault) following the most recent event on the Garlock fault (A.D. 1450-1640), and up to and including the Ridgecrest sequence. We then use these results to evaluate the influence of stress changes due to past earthquakes on a probabilistic seismic hazard model for the Garlock fault.

In our first probabilistic model, we calculate BPT (Brownian Passage Time) curves of occurrence of a M ≥ 7 event on the central segment of the Garlock fault in the next 30 years, using recurrence time and coefficient of variation values calculated from paeloseismological data. Preliminary results show a probability of occurrence in 30 years of up to 10% when we do not consider the effect of ΔCFS. This increases to about 15% when ΔCFS effects are introduced in the model.

As a next step, we will implement a more complex segmented model for the Garlock fault, where probability calculations take into account multiple possible rupture combinations.
Wave downscaling using machine learning
Authors: Santamaria Aguilar Sara , Wahl Thomas
Published: March 2020

Future changes in the wind wave climate due to atmospheric changes can intensify present erosion and flood risk. Knowledge on both mean and extreme wave climate is necessary for understanding changes in sediment dynamics and flood events at the coastline. In order to assess potential wave changes, ensemble nearshore wave projections are required for covering   the entire range of wave conditions and also the large uncertainties related to future climate states. However, nearshore wave projections are not available for most coastal regions due to the excessive computational effort required for dynamically downscaling ensemble offshore wave data. As a result, the large relative contribution of waves to coastal flooding and erosion is commonly omitted in the assessment of those hazards. In this context, machine learning models can be an efficient tool for downscaling ensemble global wave projections if they are able to accurately simulate the non-linear processes of wave propagation due to their low computational requirements. Here, we analyse the performance of three machine learning methods, namely random forest, multivariate adaptive regression splines and artificial neural networks, for downscaling the wave climate along the coast of Florida. We further compare the performance of these three models to the multiple linear regression, which is a statistical model frequently used, although it does not account for the non-linearities associated with wave propagation processes. We find that the three machine learning models perform better than the multiple linear regression for all wave parameters (significant wave height, peak and mean periods, direction) along the entire coastline of Florida, which highlights the ability of these models to reproduce the non-linear wave propagation processes. Specifically, random forest shows the best performance and the lowest computational training times. In addition, this model shows a remarkably good performance in simulating the wave extreme events compared to the other models. By following a tree bagging approach, random forest can also provide confidence intervals and reduce the tuning process. The latter is one of the main disadvantages of the artificial neural networks, which also show a high performance for wave downscaling but require more training and tuning effort. Although the significant wave height and the periods can be simulated with very high accuracy (R2 higher than 0.9 and 0.8 respectively), the wave direction is poorly simulated by all models due to its circular behaviour. We find that a transformation of the direction into sine and cosine can improve the model performance. Finally, we downscale an ensemble of global wave projections along the coast of Florida and assess potential changes in the wave climate of this region.   
The origin and fate of organic matter in circum-Arctic subglacial ecosystems
Authors: Vinsova Petra , Simpson Myrna J. , Yuan Tiange , Hajdas Irka , Falteisek Lukas , Kohler Tyler J. , Yde Jacob C. , Zarsky Jakub D. , Stibal Marek
Published: March 2020

Glacier and ice sheet beds represent important yet underresearched cryospheric ecosystems. Life in the subglacial environment is mostly dependent on organic matter (OM) overridden by ice during times of glacier advance, and the nature of subglacial OM is, therefore, likely to drive the ecosystem functionality. Here we describe the origin, degradation stage and environmental context of OM present underneath glaciers in the circum-Arctic, and their effects on the resident microbial communities.

In total, 19 glaciers from Alaska, Greenland, Iceland, Svalbard, and Norway were sampled for subglacial sediments. Biomarker analysis of the sediment samples was conducted using total solvent extraction, and copper (II) oxide (CuO) oxidation techniques yielding lipids and lignin-derived phenols. The extracts were analyzed by GC-MS to characterize the molecular-level composition of OM present. The biomarker data were then placed in the context of other environmental data, such as radiocarbon age, nutrient contents, and microbial community composition. The majority of OM in the samples was plant-derived, suggested by the dominance of long-chain n-alkanols over the microbial-specific short-chain n-alkanols. The composition of long-chain n-alkanes (≥C20), used as biomarkers for vascular plant waxes, in the solvent extracts suggested grass sources for samples from most Greenland glaciers and conifer sources for some glaciers from Norway, Alaska, and Disko Island (Qeqertarsuaq) in West Greenland. The rest of the OM in the subglacial samples was identified to have more general tree sources. The carbon preference index (CPI) of long-chain n-alkanes suggested a high degradation stage in most samples and was correlated with the radiocarbon age of the sediments’ OC (r = -0.68). Sediments containing older and more degraded OM were found to host less diverse microbial communities compared to those of the younger sites.

In a rapidly warming climate, previously glacier-covered areas are being exposed as a consequence of glacier recession. This new land is standing at the onset of ecological succession and pedogenesis. Our results contribute to the understanding of the potential ecological function of subglacial OM as an important source of carbon and driver of microbial community development after deglaciation in the circum-Arctic region.
An overview about the interaction between the underground pumped storage hydropower (UPSH) and the saturated subsurface medium: effects of the water exchanges on the environment and the plant efficiency
Authors: Pujades Estanislao
Published: March 2020

Underground pumped storage hydropower (UPSH) is an alternative energy storage system (ESS) for flat regions, where conventional pumped storage hydropower plants cannot be constructed due to topographical limitations. UPSH plants consist in two reservoirs, the upper one is located at the surface or possibly underground (but at shallow depth) while the lower one is underground. Although the underground reservoir can be drilled, the use of abandoned mines (deep or open pit mines) as underground reservoir is a more efficient alternative that is also beneficial for local communities after the cessation of mining activities. Given that mines are rarely waterproofed, water exchanges between UPSH plants and the underground medium are expected. Water exchanges may have negative consequences for the environment, but also for the feasibility of UPSH plants. The impacts on the environment and the plant efficiency may have hydraulic (changes of the natural piezometric head distribution, effects in the hydraulic head difference between the two reservoirs, etc.) or hydrochemical nature (dissolution and/or precipitation of minerals in the aquifer and in the reservoirs, corrosion of facilities, modification of pH, etc.). At this stage, it is required a sound understanding of all the impacts produced by the water exchanges and evaluate under which circumstances they are mitigated. This assessment will allow ascertaining criteria for the selection of the best places to construct future UPSH plants.
Heat Events in the Indian Subcontinent under a warming climate scenario: Detection and its Drivers
Authors: Ritika Kapoor , Scoccimarro Enrico , Alvarez-Castro Carmen , Materia Stefano , Gualdi Silvio
Published: March 2020

Global temperatures have shown a warming trend over the last century, mainly as a result of anthropogenic activities. Rising temperatures are a potential cause for increase of extreme climate events, such as heat waves, both in severity and frequency. Under an increasing extreme event scenario, the world population of mid- and low-latitude countries is more vulnerable to heat related mortality and morbidity. In India, the events occurred in recent years have made this vulnerability clear, since the numbers of heat related deaths are on a rise.

Over India, the heat waves occur during the months of April to June and can impact various sectors including health, agriculture, ecosystems and the national economy. In May 2015, a severe heat wave due to the delayed onset of southwest monsoon affected parts of south-eastern India, which claimed more than 2500 lives.

Preliminary results show the prevalence of Heat events in North-West, Central and South-Eastern regions of India during the pre-monsoon (March, April, May) and transitional (May, June, July) months. We consider the Heat Index (HI), a combination of temperature and relative humidity, also known as apparent temperature, gives an insight into the discomfort because of increment in humidity, that reduces the efficiency of body’s cooling mechanism as it blocks evaporation. Thus, along with temperature anomalies, humidity also plays a role in transitional period.

Heatwaves over India are known to be linked with El-Niño-Southern Oscillation or ENSO, but some studies indicated that the processes generating heat waves over northwest-central and coastal eastern India could be linked to anomalous blocking over North Atlantic and to the cooling over central and east equatorial Pacific. While other studies demonstrated that anomalous persistent high-pressure systems, supplemented with clear skies and depleted soil moisture, are primarily responsible for the occurrence of heat waves over India.

The changes in the frequency and intensity of extreme events have profound impact on human society and the natural environment. The heat stress and underlying anomalous conditions can exacerbate an increase in the number of deaths. While global heat wave and health impact research is prolific in some regions, the global population most incline to risk of death and conspicuous harm caused by extreme heat is under-represented. Heat wave and health impact research are needed in regions where this impact is expected to be most severe.
Specific aspects of above-ice gravimetric observations
Authors: Shklyaruk Alexey , Kuznetsov Kirill , Arutyunyan David , Lygin Ivan
Published: March 2020

Today, gravimetry is actively used in solving various detailed engineering problems, in researches of the underground fluid dynamics, etc. It is worth noting that the areas of large rivers and lakes are an interference in creating a regular network of observations, which is necessary to the above problems solution. For now the results of satellite, marine or aero surveys do not allow obtaining materials with the necessary resolution and accuracy parameters. The solution to this problem may be surveying in the winter period on frozen water reservoirs.

Gravimetric surveys were carried out on the surface of the ice covering the Ugra River as part of the field course of the Geological Faculty of Lomonosov Moscow State University in Kaluga region. Two high-precision relative gravimeters CG-5 Autograv by Scintrex Ltd were used.

During above-ice gravimetric observations, many factors influence the gravimeter. They can be divided into two groups: natural and human cause. The first group includes gusts of wind, melting ice, the flow of the river. The second group includes operator’s movements, interference of people passing by, etc.

The completed studies made it possible to evaluate the parameters of the standard deviation (SD) of the gravimeter records and the influence of the above factors on its tilt. An analysis of the observation results showed that high-precision relative gravimeters allow above-ice surveying with an accuracy of no worse than 5 μGal, which corresponds to the current level of ground gravity survey’s accuracy.

To minimize the influence of interfering factors, a special observation technique is required:

For an independent assessment of the accuracy of observations at each point, several gravimeters should be applied;

At each point, at least 10 measurements with one gravimeter should be performed;

The time of one measurement should be at least 60 seconds;

To minimize the influence of external factors on the measurements of gravimeters, it should be ensured that near the operator there are no outsiders, equipment, etc., creating oscillations of the surface which the device is installed on. At the same time, the operator of the gravimeter must constantly check the records of the gravimeter, the SD parameter and its levels.
Bayesian Inversion of Wrapped Satellite Interferometric Phase to Estimate Fault and Volcano Surface Ground Deformation Models
Authors: Jiang Yu , González Pablo
Published: March 2020

Phase unwrapping is the process of recovering the absolute phase from unambiguous wrapped phase values that are measured modulo 2pi rad. From a mathematical point of view, phase unwrapping is an inverse problem, however, it is ill-posed and notoriously difficult to solve in the presence of noise. Meanwhile, phase unwrapping errors severely impact the estimation of earthquake and volcano source parameters using interferometric observations, therefore avoiding phase unwrapping completely is desirable. 

A potential solution to avoid the unwrapping error issue completely, is to carry out a geophysical inversion directly on the wrapped phase observations. To overcome the need for phase unwrapping, we propose a novel approach that we can invert directly the interferometric wrapped phase, circumventing the ill-posed phase unwrapping processing step. This approach includes (1) a downsampling algorithm, (2) a method to estimate the covariance function of the wrapped phase, (3) an appropriate misfit function between the observed and the simulated wrapped phase. We also assess the uncertainties of source parameters within a Bayesian approach, and finally we test the robustness of the inversion methodology in multiple simulations including variable decorrelation and atmospheric noise simulations.

We demonstrate the proposed methodology on synthetic cases with variable noise and one real earthquake case. We show that the method is robust in challenging noise scenarios. We also show an improvement with the Bayesian approach in performance with respect to similar previous methods, resulting in avoiding any influence of seed starting models, and escaping local minima. We study the impact of a small percentage of incorrectly unwrapped phase observations in current state-of-the-art methods, and show that the presence of a small fraction of unwrapping errors affect strongly the estimation process. We conclude that in the cases where phase unwrapping is difficult or even impossible, the proposed inversion methodology with wrapped phase will provide an alternative approach to assess earthquake and volcano source model parameters.
Plume evolution, transport and mixing processes under highly transient boundary conditions: A laboratory-scale study
Authors: Basilio Hazas Mónica , Ziliotto Francesca , Rolle Massimo , Chiogna Gabriele
Published: March 2020

Transient boundary conditions are important in the transport of dissolved solutes and contaminants in the subsurface, as they can generate complex groundwater flow fields that influence mixing and mixing-controlled reactions. An important example of highly transient boundaries are rivers in which the river stage changes fast and sharply due to the operation of hydropower plants. In order to better understand how these rivers influence the groundwater flow field, we performed a laboratory experimental study. A quasi two-dimensional flow-through chamber was filled with glass beads and sand and the surface of the saturated porous medium was connected to two water reservoirs representing two rivers in hydraulic contact with the aquifer. The river stage could be changed independently by a separate lifting system for each reservoir. This experimental set-up was inspired by shallow unconfined aquifers in hydraulic contact with rivers affected by hydropeaking. In order to observe the influence of the transient boundary conditions, we injected a color tracer and observed the evolution of the solute plume across the tank. We monitored the spatial distribution of the tracer and the impact of the dynamic river boundaries on the groundwater plume with a non-invasive image analysis technique, consisting in a background light foil and a CCD camera. Additionally, to analyze the breakthrough curves we also took samples at multiple outlet ports and measured the tracer concentration using a spectrophotometer. We characterized the plume behavior using different metrics, including the dilution index, the flux-related dilution index and the moments of the tracer distribution. We conducted experiments both under steady-state flow conditions (with and without rivers) and under different transient conditions, obtained by variations in the order and the intensity of the river fluctuations, and groundwater flow velocities.
Evaluation of thermally driven local winds in the Swiss Alps simulated by a high-resolution NWP model
Authors: Schmidli Juerg , Ghasemi Abouzar
Published: March 2020

In fair weather conditions, thermally driven local winds often dominate the wind climatology in deep Alpine valleys resulting in a unique wind climatology for any given valley. The accurate forecasting of these local wind systems is challenging, as they are the result of complex and multi-scale interactions. Even more so, if the aim is an accurate forecast of the winds from the near-surface to the free atmosphere, which can be considered a prerequisite for the accurate prediction of mountain weather.  This study investigates the skill of a high-resolution numerical weather prediction (NWP) model, the most current version of the COSMO-DWD model,  at 1.1 km grid spacing in simulating the thermally driven local winds in the Swiss Alps for a month-long period in September 2016. The study combines the evaluation of the surface winds in several Alpine valleys with a more detailed evaluation of the wind evolution throughout the valley depth for a particular site in the Swiss Rhone valley. The former is based on a comparison with observations from the operational measurement network of MeteoSwiss, while the latter uses data from a wind profiler stationed at Sion airport.
An evaluation of tropical waves and wave forcing of the QBO in the QBOi models
Authors: Holt Laura , Lott Francois ,   QBOi Contributors
Published: March 2020

We analyze the stratospheric waves in models participating in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi). All models have robust Kelvin and mixed Rossby-gravity wave modes in winds and temperatures at and represent them better than most of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. There is still some spread among the models, especially concerning the mixed Rossby-gravity waves. We attribute the variability in equatorial waves among the QBOi models in part to the varying horizontal and vertical resolutions, to systematic biases in zonal winds, and to the considerable variability in convectively coupled waves in the troposphere among the models: only roughly half of the QBOi models have realistic convectively coupled Kelvin waves and only a few models have convectively coupled mixed Rossby-gravity waves. The models with stronger convectively coupled waves produce larger zonal mean forcing due to resolved waves in the QBO region. Finally we evaluate the Eliassen-Palm (EP) flux and EP flux divergence of the resolved waves in the QBOi models. We find that there is a large spread in the forcing from resolved waves in the QBO region, and the resolved wave forcing has a robust correlation with model vertical resolution