bluuebunny/crossref_metadata_2025 huggingface dataset:
Joint assimilation of GRACE satellite and in-situ discharge observations into a global hydrological model
Authors: Schulze Kerstin , Engels Olga , Kusche Jürgen , Gerdener Helena , Müller Schmied Hannes , Niemann Christoph , Ackermann Sebastian , Döll Petra
Published: March 2021

Global hydrological models simulate water storages and fluxes of the water cycle which is important for e.g. water management decisions and drought/flood predictions. However, the models include many uncertainties due to the model inputs (e.g. climate forcing data), model parameters, and model structure resulting in disagreements with observations. To reduce these uncertainties, the models are typically calibrated against in-situ discharge observations or GRACE-derived total water storage anomalies (TWSA) are integrated into the model by data assimilation.

In this study, we introduce a framework for jointly assimilating multiple observations into the WaterGAP 2.2d model over the Mississippi River Basin for 2003-2018. We do not only assimilate GRACE-derived TWSA but also in-situ discharge observations from gauge stations. In addition, we vary the number as well as the location of the considered discharge stations to derive information about e.g. the influence of assimilating down- or upstream stations.

Our results show a strong influence of the GRACE data and that the assimilation of multiple discharge stations resembles the results of a traditional calibration approach. We expect the most downstream stations to have a larger impact on the assimilation results than the more upstream stations (as the downstream stations already include the information of the upstream stations). The gained insights of this study show a great potential to better assess and understand the global freshwater system and become even more relevant in view of the Surface Water and Ocean Topography (SWOT) satellite. SWOT will be launched in 2022 and is expected to allow the derivation of discharge observations globally for rivers wider than 50-100m.
Imaging noise sources: comparing and combining a matched-field processing technique with finite-frequency noise source inversions
Authors: Igel Jonas , Bowden Daniel , Sager Korbinian , Fichtner Andreas
Published: March 2021

Imaging the spatio-temporal variations of ambient seismic noise sources can provide important information to improve near real-time monitoring and noise tomography. Various methods have been developed to tackle this problem. For example, Matched-Field Processing (MFP) offers an efficient data-driven approach by testing different noise source locations and subsequently correlating and stacking. A more rigorous approach is treating it as a finite-frequency full-waveform inversion problem. In contrast to the MFP technique, an inversion framework allows for the incorporation of prior information and subsequent iterative updates of the noise source distribution by numerically modelling correlations and source sensitivity kernels. Bowden et al. (2020) discuss the similarities between these two methods and how one can be derived from the other. 

We aim to compare and contrast the two methods using real data from a regional to a global scale to locate the secondary microseismic sources in the ocean. Igel et al. (2021, in prep) use a logarithmic energy ratio as measurement for the sensitivity kernels, which is chosen due to its robustness with respect to unknown 3D Earth structures. However, some disadvantages of this type of measurement are not considering absolute amplitudes and discarding information outside of the expected surface wave arrival time window. By combining the two methods and first using MFP to create an initial model for the inversion, we are able to steer the inversion in the right direction, allowing us to use a more elaborate full-waveform measurement in the inversion and hence increasing the resolution and quality of the final model. 

Results for noise source inversions in the ocean on a daily basis using the combination of the two methods will be presented. This work paves the way for publicly available, daily, multi-scale ambient noise source maps.
Mapping gravel beds combining multibeam bathymetry, underwater video, and grab samples with continuous spatial modeling by random forest
Authors: Montereale Gavazzi Giacomo , Van Lancker Vera , Degraer Steven
Published: March 2021

In this study, high-resolution (1 m) multibeam echosounder system (MBES) bathymetry data and derivatives, optical images by underwater video drop-frame, and Hamon grab sediment samples, all acquired within 170 km2 of seafloor in offshore Belgian Waters, were integrated to produce a random forest spatial model targeting the prediction of the continuous surficial distribution of gravel %, i.e., a substrate category whose known detailed distribution is central to the environmental stewardship of natural gravel bed habitat. MBES bathymetry reveals explicit details of the seafloor topography, allowing the derivation of geomorphometric variables that are important in the classification process. Underwater video and grab samples provide the means to directly observe the nature and distribution of the response variable. The model output is presented along with a protocol of error and uncertainty estimation, providing detailed information of the gravel spatial distribution that would otherwise remain undetected by categorical-type classifications, focused on predefined habitat classification schemes. Targeting the methodological improvement of this mapping approach, an overview of the limitations identified at the various steps of the acoustic seafloor classification (ASC) pipeline is presented.
Rotating shallow water flow under location uncertainty with a structure-preserving discretization
Authors: Brecht Rüdiger , Li Long , Bauer Werner , Mémin Etienne
Published: March 2021

We introduce a new representation of the rotating shallow water equations based on a stochastic transport principle. The derivation relies on a decomposition of the fluid flow into a large-scale component and a noise term that models the unresolved small-scale flow. The total energy of such a random model is demonstrated to be preserved along time for any realization. Thus, we propose to combine a structure-preserving discretization of the underlying deterministic model with the discrete stochastic terms. This way, our method can directly be used in existing dynamical cores of global numerical weather prediction and climate models. For an inviscid test case on the f-plane we use a homogenous noise and illustrate that the spatial part of the stochastic scheme preserves the total energy of the system. Finally, using an inhomogenous noise, we show  that the proposed random model better captures the structure of a large-scale flow than a comparable deterministic model for a barotropically unstable jet on the sphere.
Coupled dynamics of primordial and recycled heterogeneity in Earth's lower mantle, and their present-day seismic signatures
Authors: Gülcher Anna J. P. , Ballmer Maxim D. , Tackley Paul J.
Published: March 2021

The nature of compositional heterogeneity in Earth’s lower mantle is a long-standing puzzle that can inform about the thermochemical evolution and dynamics of our planet. On relatively small scales (<1km), streaks of recycled oceanic crust (ROC) and lithosphere are distributed and stirred throughout the mantle, creating a “marble cake” mantle. On larger scales (10s-100s of km), compositional heterogeneity may be preserved by delayed mixing of this marble cake with either intrinsically-dense or -strong materials of e.g. primordial origin. Intrinsically-dense materials may accumulate as piles at the core-mantle boundary, while intrinsically viscous (e.g., enhanced in the strong mineral MgSiO3 bridgmanite) may survive as blobs in the mid-mantle for large timescales (i.e., as plums in the mantle “plum pudding”). So far, only few, if any, studies have quantified mantle dynamics in the presence of different types of heterogeneity with distinct physical properties.

Here, we use 2D numerical models of global-scale mantle convection to investigate the coupled evolution and mixing of (intrinsically-dense) recycled and (intrinsically-strong) primordial material. We explore the effects of ancient compositional layering of the mantle, as motivated by magma-ocean solidification studies, and the physical parameters of the primordial material. Over a wide parameter range, primordial and recycled heterogeneity is predicted to coexist with each other. Primordial material usually survives as mid-to-large scale blobs in the mid-mantle, and this preservation is largely independent on the initial primordial-material volume. In turn, recycled oceanic crust (ROC) persists as piles at the base of the mantle and as small streaks everywhere else. The robust coexistence between recycled and primordial materials in the models indicate that the modern mantle may be in a hybrid state between the “marble cake” and “plum pudding” styles.

Finally, we put our model predictions in context with geochemical studies on early Earth dynamics as well as seismic discoveries of present-day lower-mantle heterogeneity. For the latter, we calculate synthetic seismic velocities from output model fields, and compare these synthetics to tomography models, taking into account the limited resolution of seismic tomography. Because of the competing effects of compositional and thermal anomalies on S-wave velocities, it is difficult to identify mid-mantle bridgmanitic domains in seismic tomography images. This result suggests that, if present, bridgmanitic domains in the mid-mantle may be “hidden” from seismic tomographic studies, and other approaches are needed to establish the presence/absence of these domains in the present-day deep Earth.
Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones
Authors: Martín Ariadna , Amores Angel , Orfila Alejandro , Marcos Marta
Published: March 2021

Every year the Caribbean Sea faces the passage of powerful tropical cyclones that generate coastal extreme sea levels with potential strong and hazardous impacts. In this work we simulate the storm surges and wind-waves induced by a set of over 1000 tropical cyclones over the Caribbean Sea that are representative of the present-day climate and that have been extracted from a global database of synthetic hurricanes spanning a 10,000-year period. The atmospheric forcing fields, built from the synthetic tropical cyclones, are used to feed a fully coupled hydrodynamic-wave model with high resolution (~1 km) along the continental and island coasts. Given the large number of events modelled, the outputs allow detailed statistical analyses of the magnitude and mechanisms of coastal extreme sea levels as well as the identification of most exposed areas to both storm surges and large wind-waves.
Influence of the hydrodynamics in spatio-temporal variability of clorophyll a in a small-scale and microtidal bay: Fangar Bay case (Ebro Delta)
Authors: F-Pedrera Balsells Marta , Grifoll Manel , Fernández-Tejedor Margarita , Espino Manuel , Sánchez-Arcilla Agustín
Published: March 2021

Estuaries and coastal bays are areas of large spatial-temporal variability in physical and biological variables due to environmental factors such as local wind, light availability, freshwater inputs or tides. The physical characteristics of an estuary affect its hydrodynamics. These in turn modify the behaviour of biological variables such as the concentration of chlorophyll a (Chl a). In a small-scale, micro tidal bay such as the Fangar Bay (Ebro Delta), hydrodynamics is influenced above all by local winds, as well as by fresh water contributions. The results of two field campaigns and Sentinel-2 images show how the concentration of Chl a is affected by strong wind episodes typical of this area (NW-E winds). With these episodes of strong wind (> 10 m-s-1) mixing occurs in the water column causing an increase in the concentration of Chl a. On the other hand, with sea breezes (< 6 m-s-1) the water column is stratified causing a decrease in the Chl a concentration. However, the spatial-temporal variability of Chl a in small-scale estuaries and coastal bays is quite complex due to the many factors involved and deserves more intensive field campaigns and additional numerical modelling efforts.
Toward CO2 and CH4 measurements by ground-based observations of surface-scattered sunlight
Authors: Hemmer Benedikt , Proß Christin , Sander Stanley P. , Pongetti Thomas J. , Zeng Zhao-Cheng , Hase Frank , Kostinek Julian , Kleinschek Ralph , Butz André
Published: March 2021

Precise knowledge of sources and sinks in the carbon cycle is desired to understand its sensitivity to climate change and to account and verify man-made emissions. In this context, extended sources like urban areas play an important role. While in-situ measurements of carbon dioxide (CO2) and methane (CH4) are highly accurate but localized, satellites measure column-integrated concentrations over an extended footprint. The CLARS-FTS [1, 2] stationed at the Mt. Wilson observatory looking downward into the Los Angeles basin has pioneered an innovative measurement technique that fills the sensitivity gap between in-situ and satellite measurements. The technique enables mapping the urban greenhouse gas concentration fields by collecting spectra of ground scattered sunlight and scanning through the region.

 

Here, we report on progress developing a portable setup for a CLARS-FTS-like measurement geometry. The instrument is based on the EM27/SUN FTS with a modified pointing technique and a more sensitive detector. The retrieval algorithm is based on the RemoTeC software, previously employed for solar backscatter satellite measurements. We discuss first steps in terms of instrument performance and retrieval exercises. For the latter, we have carried out simulations on how the neglect of scattering by the retrieval affects the retrieved boundary layer concentrations of CO2 and CH4 for an ensemble of hypothetical scenes with variable complexity in aeorsol loadings and viewing geometry. We also report on a test to apply RemoTeC to a small set of CLARS-FTS spectra collected throughout the Los Angeles basin.

 

References

[1] Fu, D. et al., 2014: Near-infrared remote sensing of Los Angeles trace gas distributions from a mountaintop site, Atmos. Meas. Tech., 7, 713–729, https://doi.org/10.5194/amt-7-713-2014

[2] Wong, K. W. et al., 2015: Mapping CH4 : CO2 ratios in Los Angeles with CLARS-FTS from Mount Wilson, California, Atmos. Chem. Phys., 15, 241–252, https://doi.org/10.5194/acp-15-241-2015
High-resolution near-surface soil moisture through the combination of Sentinel-1 and Cosmic-Ray Neutron Probe in a Mediterranean agroforestry
Authors: Taghavi Bayat Aida , Schönbrodt-Stitt Sarah , Nasta Paolo , Ahmadian Nima , Conrad Christopher , Bogena Heye R. , Vereecken Harry , Jakobi Jannis , Baatz Roland , Romano Nunzio
Published: March 2021

The precise estimation and mapping of the near-surface soil moisture (~5cm, SM5cm) is key to supporting sustainable water management plans in Mediterranean agroforestry environments. In the past few years, time series of Synthetic Aperture Radar (SAR) data retrieved from Sentinel-1 (S1) enable the estimation of SM5cm at relatively high spatial and temporal resolutions. The present study focuses on developing a reliable and flexible framework to map SM5cm in a small-scale agroforestry experimental site (~30 ha) in southern Italy over the period from November 2018 to March 2019. Initially, different SAR-based polarimetric parameters from S1 (in total 62 parameters) and hydrologically meaningful topographic attributes from a 5-m Digital Elevation Model (DEM) were derived. These SAR and DEM-based parameters, and two supporting point-scale estimates of SM5cm were used to parametrize a Random Forest (RF) model. The inverse modeling module of the Hydrus-1D model enabled to simulate two  supporting estimates of SM5cm by using i) sparse soil moisture data at the soil depths of 15 cm and 30 cm acquired over 20 locations comprised in a SoilNet wireless sensor network (SoilNet-based approach), and ii) field-scale soil moisture monitored by a Cosmic-Ray Neutron Probe (CRNP-based approach). In the CRNP-based approach, the field-scale SM5cm was further downscaled to obtain point-scale supporting SM5cm data over the same 20 positions by using the physical-empirical Equilibrium Moisture from Topography (EMT) model. Our results show that the CRNP-based approach can provide reasonable SM5cm retrievals with RMSE values ranging from 0.034 to 0.050 cm³ cm-3 similar to the ones based on the SoilNet approach ranging from 0.029 to 0.054 cm³ cm-3. This study highlights the effectiveness of integrating S1 SAR-based measurements, topographic attributes, and CRNP data for mapping SM5cm at the small agroforestry scale with the advantage of being non-invasive and easy to maintain.

 
Assessing Floods and Droughts direct impacts in sub-Saharan Africa by using a regional hydrologic model: a fully probabilistic approach
Authors: Simone Gabellani , Rudari Roberto ,   CIMA, VU and WUR Team
Published: March 2021

Over the last few decades, disasters resulting from natural hazards have often derailed hard-earned development progress. This is especially true in developing countries such as in sub-Saharan Africa which was the object of this study. The majority of disasters in Africa are hydro-meteorological in origin, with droughts affecting the largest number of people and floods occurring frequently along major river systems and in many urban areas. Disasters, however, can be significantly minimised with rigorous understanding of the risk, obtained using scientific risk modelling and through effective institutional and community prevention, mitigation and preparedness. Specifically, this study focuses on the risk assessment due to both Floods and Droughts in 16 countries in Sub-Saharan Africa. The study describes the crucial role of a physically based regional hydrologic model as a common engine to assess drought and flood hazard and their subsequent risk implications on people and economy. The hydrologic simulations are at the basis of the fully probabilistic approach adopted in the study. The study develops risk estimates in both current and future climate conditions, using RCP8.5 projections, paired with socio economic development (i.e., considering population and GDP growth). Results are discussed in terms of impacts on population and different key sectors of the African economy, such as agriculture and infrastructure, while especially focusing on the direct economic losses caused by flood and drought disasters and on the  food security implications of drought disasters.
Probabilistic Tephra Hazard Assessment of Campi Flegrei, Italy
Authors: Martínez Montesinos Beatriz , Titos Manuel , Sandri Laura , Barsotti Sara , Macedonio Giovanni , Costa Antonio
Published: March 2021

Campi Flegrei is an active volcano located in one of the most densely inhabited areas in Europe and under high-traffic air routes. There, the Vesuvius Observatory’s surveillance system, which continuously monitors volcanic seismicity, soil deformations and gas emissions, highlights some variations in the state of the volcanic activity. It is well known that fragmented magma injected into the atmosphere during an explosive volcanic eruption poses a threat to human lives and air-traffic. For this reason, powerful tools and computational resources to generate extensive and high-resolution hazard maps taking into account a wide spectrum of events, including those of low probability but high impact, are important to provide decision makers with quality information to develop short- and long- term emergency plans. To this end, in the framework of the Center of Excellence for Exascale in Solid Earth (ChEESE), we show the potential of HPC in Probabilistic Volcanic Hazard Assessment. On the one hand, using the ChEESE's flagship Fall3D numerical code and taking advance of the PRACE-awarded resources at CEA/TGCC-HPC facility in France, we perform thousands of simulations of tephra deposition and airborne ash concentration at different flight levels exploring the natural variability and uncertainty on the eruptive conditions on a 3D-grid covering a 2 km-resolution 2000 km x 2000 km computational domain. On the other hand, we create short- and long-term workflows, by updating current Bayesian-Event-Tree-Analysis-based prototype tools, to make them capable of analyze the large amount of information generated by the Fall3D simulations that finally gives rise to the hazard maps for Campi Flegrei.
Global fine resolution mapping of ozone metrics through explainable machine learning
Authors: Betancourt Clara , Stadtler Scarlet , Stomberg Timo , Edrich Ann-Kathrin , Patnala Ankit , Roscher Ribana , Kowalski Julia , Schultz Martin G.
Published: March 2021

Through the availability of multi-year ground based ozone observations on a global scale, substantial geospatial meta data, and high performance computing capacities, it is now possible to use machine learning for a global data-driven ozone assessment. In this presentation, we will show a novel, completely data-driven approach to map tropospheric ozone globally.

Our goal is to interpolate ozone metrics and aggregated statistics from the database of the Tropospheric Ozone Assessment Report (TOAR) onto a global 0.1° x 0.1° resolution grid.  It is challenging to interpolate ozone, a toxic greenhouse gas because its formation depends on many interconnected environmental factors on small scales. We conduct the interpolation with various machine learning methods trained on aggregated hourly ozone data from five years at more than 5500 locations worldwide. We use several geospatial datasets as training inputs to provide proxy input for environmental factors controlling ozone formation, such as precursor emissions and climate. The resulting maps contain different ozone metrics, i.e. statistical aggregations which are widely used to assess air pollution impacts on health, vegetation, and climate.

The key aspects of this contribution are twofold: First, we apply explainable machine learning methods to the data-driven ozone assessment. Second, we discuss dominant uncertainties relevant to the ozone mapping and quantify their impact whenever possible. Our methods include a thorough a-priori uncertainty estimation of the various data and methods, assessment of scientific consistency, finding critical model parameters, using ensemble methods, and performing error modeling.

Our work aims to increase the reliability and integrity of the derived ozone maps through the provision of scientific robustness to a data-centric machine learning task. This study hence represents a blueprint for how to formulate an environmental machine learning task scientifically, gather the necessary data, and develop a data-driven workflow that focuses on optimizing transparency and applicability of its product to maximize its scientific knowledge return.
LOFAR observations of a jet-driven piston shock in the low solar corona
Authors: Maguire Ciara , Carley Eoin , Zucca Pietro , Vilmer Nicole , Gallagher Peter
Published: March 2021

The Sun produces highly dynamic and eruptive events that can drive shocks through the corona. These shocks can accelerate electrons, which result in plasma emission in the form of a type II radio burst. Despite a large number of type II radio bursts observations, the precise origin of coronal shocks is still subject to investigation. Here we present a well-observed solar eruptive event that occurred on 16 October 2015, focusing on a jet observed in the extreme ultraviolet by the SDO Atmospheric Imaging Assembly, a streamer observed in white-light by the Large Angle and  Spectrometric Coronagraph, and a metric type II radio burst observed by the LOw-Frequency Array (LOFAR) radio telescope. For the first time, LOFAR has interferometrically imaged the fundamental and harmonic sources of a type II radio burst and revealed that the sources did not appear to be co-spatial, as would be expected from the plasma emission mechanism. We correct for the separation between the fundamental and harmonic using a model which accounts for the scattering of radio waves by electron density fluctuations in a turbulent plasma. This allows us to show the type II radio sources were located ∼0.5 Rsun above the jet and propagated at a speed of ∼1000 km s−1, which was significantly faster than the jet speed of ∼200 km s−1. This suggests that the type II burst was generated by a piston shock driven by the jet in the low corona.
Snow microstructure on sea ice: Importance for remote sensing applications
Authors: Macfarlane Amy R. , Arndt Stefanie , Dadic Ruzica , Gabarró Carolina , Light Bonnie , Mahmud Mallik , Naderpour Reza , Scharien Randall , Smith Madison , Spreen Gunnar , Stroeve Julienne , Tavri Aikaterini , Wagner David N. , Schneebeli Martin
Published: March 2021

Snow plays a key role in interpreting satellite remote sensing data from both active and passive sensors in the high Arctic and therefore impacts retrieved sea ice variables from these systems ( e.g., sea ice extent, thickness and age). Because there is high spatial and temporal variability in snow properties, this porous layer adds uncertainty to the interpretation of signals from spaceborne optical sensors, microwave radiometers, and radars (scatterometers, SAR, altimeters). We therefore need to improve our understanding of physical snow properties, including the snow specific surface area, snow wetness and the stratigraphy of the snowpack on different ages of sea ice in the high Arctic.

The MOSAiC expedition provided a unique opportunity to deploy equivalent remote sensing sensors in-situ on the sea ice similar to those mounted on satellite platforms. To aid in the interpretation of the in situ remote sensing data collected, we used a micro computed tomography (micro-CT) device. This instrument was installed on board the Polarstern and was used to evaluate geometric and physical snow properties of in-situ snow samples.  This allowed us to relate the snow samples directly to the data from the remote sensing instruments, with the goal of improving interpretation of satellite retrievals. Our data covers the full annual evolution of the snow cover properties on multiple ice types and ice topographies including level first-year (FYI), level multi-year ice (MYI) and ridges.

First analysis of the data reveals possible uncertainties in the retrieved remote sensing data products related to previously unknown seasonal processes in the snowpack. For example, the refrozen porous summer ice surface, known as surface scattering layer, caused the formation of a hard layer at the multiyear ice/snow interface in the winter months, leading to significant differences in the snow stratigraphy and remote sensing signals from first-year ice, which has not experienced summer melt, and multiyear ice. Furthermore, liquid water dominates the extreme coarsening of snow grains in the summer months and in winter the temporally large temperature gradients caused strong metamorphism, leading to brine inclusions in the snowpack and large depth hoar structures, all this significantly influences the signal response of remote sensing instruments.
Improved modelling of the present-day Greenland firn layer
Authors: Brils Max , Kuipers Munneke Peter , van de Berg Willem Jan , Heilig Achim , Vandercrux Baptiste , van den Broeke Michiel
Published: March 2021

Recent studies indicate that a declining surface mass balance will dominate the Greenland Ice Sheet’s (GrIS) contribution to 21st century sea level rise. It is therefore crucial to understand the liquid water balance of the ice sheet and its response to increasing temperatures and surface melt if we want to accurately predict future sea level rise. The ice sheet firn layer covers ~90% of the GrIS and provides pore space for storage and refreezing of meltwater. Because of this, the firn layer can retain up to ~45% of the surface meltwater and thus act as an efficient buffer to ice sheet mass loss. However, in a warming climate this buffer capacity of the firn layer is expected to decrease, amplifying meltwater runoff and sea-level rise. Dedicated firn models are used to understand how firn layers evolve and affect runoff. Additionally, firn models are used to estimate the changing thickness of the firn layer, which is necessary in altimetry to convert surface height change into ice sheet mass loss.

Here, we present the latest version of our firn model IMAU-FDM. With respect to the previous version, changes have been made to the handling of the freshly fallen snow, the densification rate of the firn and the conduction of heat. These changes lead to an improved representation of firn density and temperature. The results have been thoroughly validated using an extensive dataset of density and temperature measurements that we have compiled covering 126 different locations on the GrIS. Meltwater behaviour in the model is validated with upward-looking GPR measurements at Dye-2. Lastly, we present an in-depth look at the evolution firn characteristics at some typical locations in Greenland.

Dedicated, stand-alone firn models offer various benefits to using a regional climate model with an embedded firn model. Firstly, the vertical resolution for buried snow and ice layers can be larger, improving accuracy. Secondly, a stand-alone firn model allows for spinning up the model to a more accurate equilibrium state. And thirdly, a stand-alone model is more cost- and time-effective to use. Firn models are increasingly capable of simulating the firn layer, but areas with large amounts of melt still pose the greatest challenge.
Sources and Transport of Black Carbon number size distribution at Zeppelin Observatory, Svalbard
Authors: Cremer Roxana , Tunved Peter , Partridge Daniel , Ström Johan
Published: March 2021

Black carbon (BC) particles originate from incomplete combustion of biomass and fossil fuels. They are known to contribute to the warming of Earth’s climate due to radiative effects and aerosol-cloud interactions. The lifetime of sub-micron BC in the troposphere is in the order of days-weeks. Through interaction with other airborne compounds, the hydrophobic nature of BC gradually becomes more hygroscopic and thus available as CCN.

An assessment of the large-scale impact on clouds and climate requires detailed insights about the lifecycle of BC in the atmosphere, understanding sources for BC, transport, transformation, and removal processes. All these processes are tightly linked to particle size, making knowledge regarding how BC distributes over a given size range substantial.

In a previous study we explored statistical methods to attribute BC mass according to particle size (in review). Combining these results with cluster analysis of long term record of aerosol number size distribution (NSD) observations from Zeppelin Observatory it was shown that the method produced reasonable results for a majority of observations. However, the cluster characteristic of NSD associated with high level of pollution presented additional challenges as the methodological approach gave an unrealistic average BC size distribution.

In the current study we focus on these inconsistencies; additional analytical methods are introduced to resolve source-receptor relationships, defining transport characteristics using extensive trajectory analysis. The analysis provides insights of the processes along the travel path to the receptor location and resolves key transport routes for the BC fraction to the Arctic.
21st century nutrient and oxygen dynamics in the Gulf of Bothnia
Authors: Ruvalcaba Baroni Itzel , Hieronymus Jenny , Fredriksson Sam , Arneborg Lars
Published: March 2021

The Gulf of Bothnia is the only sub-basin of the Baltic Sea with no serious eutrophication. However, long-term observations have shown degradation of the water quality over the past years, indicating warning signals for the future. Here, we use a high resolution ocean circulation model including biogeochemistry to study 21st century nutrient and oxygen changes in the Gulf of Bothnia. We analyze ensembles for 5 different scenarios; a historical (1975-2005) and 4 future projections (2006-2100). For the projections, two atmospheric pCO2 trajectories are used, RCP4.5 and RCP8.5, and two settings for nutrient loads are applied to each RCP scenario: one following the Baltic Sea Action Plan (BSAP) and the other assuming business as usual. We also test a historical scenario but with no local nutrient loads to better understand the biogeochemical influence of the lateral open boundary. The comparison of observations with the historical scenario shows that oxygen trends are well captured by the model despite a small bias in nutrient concentrations. Our results suggest that the Bothnian Bay is more sensitive to river loads than the Bothnian Sea, which is primarily affected by the inflows from the Baltic proper. All future projections show a decrease in phosphate concentrations and an increase in nitrate concentrations due to lower/higher input of phosphate/nitrate from the Baltic proper. Oxygen concentrations in bottom waters of the Gulf of Bothnia are not susceptible to become hypoxic in the future. However, when business as usual is applied for nutrient loads, oxygen concentrations decrease significantly over the entire future period and short episodes of low oxygen conditions in bottom waters (with less than 5 ml O2/l) become more frequent and more pronounced in the Bothnian Sea, especially towards the end of the century.

 
Bioavailability and geochemical forms of Pb and Zn in Kosovo contaminated soils 
Authors: Miano Teodoro , Mondelli Donato , Piscitelli Lea , Voca Hana , D'Orazio Valeria
Published: March 2021

Mitrovica area (northern Kosovo) presents contamination by PTE in agricultural soils caused by smelter emissions and their transfer and accumulation in cultivated plants. Soil A and B, sampled from two sites in Mitrovica municipality, showed a total content of Pb and Zn of 2153 and 3087 mg kg-1, and 3214 and 4619 mg kg-1. A pot experiment was performed to understand the phytoremediation potential of two non-food crops (Sorghum bicolor L. Moench and Brassica napus Westar), chosen for their economic importance and heavy metal accumulation capacities. Bioconcentration factor, translocation factor and tolerance Indexes clearly indicated a better performance of canola in tolerating Pb and Zn, especially in soil B, even if contained higher amounts of both metals. To evaluate different chemical and physical forms of Pb and Zn in the two soils, a modified BCR extraction scheme was employed to determine amounts bound to different soil components: exchangeable fraction (acid-soluble, carbonate and exchangeable bound), reducing fraction (metal bound to Fe- or Mn-oxides), oxidizable fraction (organic and sulphide bound), and residual fraction (strongest binding with crystalline structure). A comparison of the sum of Pb and Zn concentrations obtained from BCR relative to total digestion values (pseudo-total concentrations) showed recoveries close to 100%. Very small amounts of Pb were released during step 1 (exchangeable fraction) (6,86% - soil A and 2,12% - soil B). The highest concentration of Pb, 62,62% in soil A and 56,68% in soil B, decreased in the reducing fraction (step 2), probably occurring mainly as forms bound to Fe/Mn oxides. Step 3 (oxidizable-organic matter “OM” and sulphides) released amounts of 23,15% and 20,32% of total Pb in soil A and B. Residual fraction presented very different amounts of Pb (7,87% in soil A and 20,88% in soil B). Unlike Pb, no important differences were found in the distribution of Zn among the various fraction of the two soils, with the greater amounts contained in the exchangeable fraction of both soils, 31.11% in soil A and 21.92% in soil B. Very small amounts of Zn were released during step 2 (19,3% in soil A and 22,27% in soil B) whereas step 3 released the highest amounts of Zn in both soils (36,56% in A and 40,17% in B). Residual fraction presents similar amounts of total Zn, 13,03% in A e 15,64% in B, showing an opposite trend with respect to Pb. So, a major portion of total Pb was associated to the reducing fraction, while Zn was found mostly in oxidable one, indipendent on the origin of samples. Pb strongly interacts with Fe-/Mn oxides, and, in soil B, a greater amount is immobilized in the residual fraction. These results suggest lower mobility and bioavailability of Pb in soil B with respect to soil A, partially explaining the pot experiment.
Repeatable and reproducible workflows using the RENKU open science platform
Authors: Krieger Louis , Nijzink Remko , Thakur Gitanjali , Ramakrishnan Chandrasekhar , Roskar Rok , Schymanski Stan
Published: March 2021

Good scientific practice requires good documentation and traceability of every research step in order to ensure reproducibility and repeatability of our research. However, with increasing data availability and ability to record big data, experiments and data analysis become more complex. This complexity often requires many pre- and post-processing steps that all need to be documented for reproducibility of final results. This poses very different challenges for numerical experiments, laboratory work and field-data analysis. The platform Renku (https://renkulab.io/), developed by the Swiss Data Science Center, aims at facilitating reproducibility and repeatability of all these scientific workflows. Renku stores all data, code and scripts in an online repository, and records in their history how these files are generated, interlinked and modified. The linkages between files (inputs, code and outputs) lead to the so-called knowledge graph, used to record the provenance of results and connecting those with all other relevant entities in the project.

We will discuss here several use examples, including mathematical analysis, laboratory experiments, data analysis and numerical experiments, all related to scientific projects presented separately. Reproducibility of mathematical analysis is facilitated by clear variable definitions and a computer algebra package that enables reproducible symbolic derivations. We will present the use of the Python package ESSM (https://essm.readthedocs.io) for this purpose, and how it can be integrated into a Renku workflow. Reproducibility of laboratory results is facilitated by tracking of experimental conditions for each data record and instrument re-calibration activities, mainly through Jupyter notebooks. Data analysis based on different data sources requires the preservation of links to external datasets and snapshots of the dataset versions imported into the project, that is facilitated by Renku. Renku also takes care of clear links between input, code and output of large numerical experiments, our last use example, and enables systematic updating if any of the input or code files are changed.

These different examples demonstrate how Renku can assist in documenting the scientific process from input to output and the final paper. All code and data are directly available online, and the recording of the workflows ensures reproducibility and repeatability.
Machine learning emulation of gravity wave drag in numerical weather forecasting
Authors: Chantry Matthew , Hatfield Sam , Duben Peter , Polichtchouk Inna , Palmer Tim
Published: March 2021

We assess the value of machine learning as an accelerator for a kernel of an operational weather forecasting system, specifically the parameterisation of non-orographic gravity wave drag. Emulators of this scheme can be trained that produce stable and accurate results up to seasonal forecasting timescales. By training on an increased complexity version of the parameterisation scheme we build emulators that produce more accurate forecasts than the existing parameterisation scheme. Leveraging the differentiability of neural networks we generate tangent linear and adjoint versions of our parameterisation, key components in 4D-var data-assimilation. We test our tangent linear and adjoint codes within an operational-like 4D-var setup and find no degradation in skill vs hand-written tangent-linear and adjoint codes.
The origin of elevated low-relief surfaces in the Eastern Alps from geomorphic criteria and cosmogenic nuclide dating
Authors: Gradwohl Gerit , Stüwe Kurt , Liebl Moritz , Robl Jörg
Published: March 2021

Elevated low-relief surfaces are peculiar landforms found in many areas across the Eastern Alps, most notably on the plateaus of the Northern Calcareous Alps and the southern metamorphic ranges from Nock Mountains to Koralpe. Found in domains both glaciated and unglaciated during the Pleistocene, (peri-)glacial erosion as well as fluvial prematurity have been cited as two opposing models for their formation. In order to contribute to this debate, we present a map of the existing low-relief surfaces in the Eastern Alps, bridging both glaciated and unglaciated regions, using a combined effort of field mapping and GIS-based mapping. Hypsometric statistics and analysis of longitudinal channel profiles show clear differences between formerly glaciated, partly-glaciated and unglaciated regions and their relations to the mapped surfaces. Furthermore, the pace of late- to post-Miocene incision is quantified via cosmogenic nuclide dating (26Al, 10Be, 21Ne) of allogenic siliceous sediments from discrete elevations correlating with the low-relief surfaces, in particular from cave sediments in the Northern Calcareous Alps. This information can be used to demonstrate that low-relief surfaces in many unglaciated regions, but also in some glaciated regions can be interpreted in terms of pre-Pleistocene relict landscapes.
Enhanced volatilization and redistribution of volatile organic compounds (VOCs) in contaminated aquifers subject to borehole thermal energy storage:  Model development and applications
Authors: Meng Boyan , Beyer Christof , Kolditz Olaf , Shao Haibing
Published: March 2021

In urban areas where the shallow subsurface is used for thermal energy storage (TES), interactions between the introduced heat and groundwater pollution caused by toxic organic contaminants can be expected. Temperature elevations may affect the transfer of these volatile organic compounds (VOCs) from the groundwater to the unsaturated zone, creating a redistribution or release of the contaminants in/from the subsurface environment. Such effects are particularly important considering the intersection of the unsaturated zone with the land surface and the remediation capacity of polluted aquifers. In this work, a non-isothermal multi-component two-phase flow model was developed to investigate the thermally induced volatilization and migration of the VOCs in contaminated aquifers. The numerical model, which is implemented in the open source framework OpenGeoSys-6, is able to simulate temperature-dependent mass and heat transfer processes in partially-saturated soils while allowing for phase change. Verification of the model against various benchmark problems and experimental data showed good accuracy. Simulation results revealed that a temperature-driven migration of dissolved trichloroethylene (TCE) from the groundwater to the drier regions of the unsaturated zone can be observed in general. A temperature increase of 20 K around the borehole led to a maximum decline of the total TCE concentration by 63% assuming zero TCE concentration at the soil surface. In addition, the TCE concentration distribution varied considerably with the depth-dependent water saturation. Further investigations were carried out to study the effects of different parameters, e.g. groundwater velocity, contaminant type and boundary conditions. Based on our analysis, the planning of subsurface TES systems can be optimized to account for the possible interactions with pre-existing groundwater contamination.

References:

Kolditz, O., Bauer, S., Bilke, L., Böttcher, N., Delfs, J. O., Fischer, T., ... & Zehner, B. (2012). OpenGeoSys: an open-source initiative for numerical simulation of thermo-hydro-mechanical/chemical (THM/C) processes in porous media. Environmental Earth Sciences, 67(2), 589-599.
Gaia the artist --  towards a unified higher-dimensional paradigm of life and beauty
Authors: C.-Z.-Quehenberger Renate
Published: March 2021

The Gaia hypothesis as an ecological hypothesis is proposing that the biosphere and the physical components of the Earth (atmosphere, cryosphere, hydrosphere and lithosphere) are closely integrated to form a complex interacting system that maintains the climatic and biogeochemical conditions on Earth in a preferred homeostasis. Although successful within the current scientific paradigm the explanation of „planetary sentience, or sensitivity“ becomes extremely difficult. As Hegel said, pure truth about nature is only perceivable by a poetic method.

Therefor we are proclaiming Gaia, the Earth as a female artist -- as advocated by 16th century scholar Giordano Bruno. This would imply to include such nonscientific categories as beauty, creativity and cosmic consciousness. Hence a unified Gaia theory would require a new scientific paradigm.

Based on a previously proposed higher dimensional spacial model  (Gaia 5.0) as „pattern that connects“ that explains the Earth’ intrinsic dynamics we aim to extend  our concept to the question of cognition and planetary sentience, or sensitivity. 

Hence we claim that  Gaia theory needs an extension of categories in order to understand the full scope of this spectacular place of livelihood and beauty.

Therefor we examine he prevalent relational biology that tries to overcome Newtonian point mechanics by relying on Aristotle’s „formal causes“ of the autopoietic organization and (M,R)-system as conceptualized by R. Rosen who refers to a mathematical structure, e.g. mapping of functions. Distinct to differential geometry we suggest as previously introduced higher dimensional geometrical framework (Gaia 5.0) a hyper-Euclidean geometry that allows to understand complex systems based on group theory providing all kinds of symmetries in nature based on a spacial continuum.

As a consequence we must not rely on thermodynamic premisses and life and tornados don’t belong to the same class of naturally complex systems. Instead we refer to Schrödinger’s description of a living cell as 4-dimensional entity. Based on complex number spaces we may seek  for further distinctions of processes and define ordered structures based on number theory.

Based on this we try to understand anticipatory systems by assigning Bayesian networks to (hyper-) complex number spaces. -- Hence Gaia is not playing dice but takes a random walk in Monte Carlo.
Effective Diahaline Diffusivities in Estuaries
Authors: Burchard Hans , Gräwe Ulf , Klingbeil Knut , Koganti Nicky , Lange Xaver , Lorenz Marvin
Published: March 2021

The present study aims to estimate effective diahaline turbulent salinity fluxes and diffusivities in numerical model simulations of estuarine scenarios. The underlying method is based on a quantification of salinity mixing per salinity class, which is shown to be twice the turbulent salinity transport across the respective isohaline. Using this relation, the recently derived universal law of estuarine mixing, predicting that average mixing per salinity class is twice the respective salinity times the river run‐off, can be directly derived. The turbulent salinity transport is accurately decomposed into physical (due to the turbulence closure) and numerical (due to truncation errors of the salinity advection scheme) contributions. The effective diahaline diffusivity representative for a salinity class and an estuarine region results as the ratio of the diahaline turbulent salinity transport and the respective (negative) salinity gradient, both integrated over the isohaline area in that region and averaged over a specified period. With this approach, the physical (or numerical) diffusivities are calculated as half of the product of physical (or numerical) mixing and the isohaline volume, divided by the square of the isohaline area. The method for accurately calculating physical and numerical diahaline diffusivities is tested and demonstrated for a three‐dimensional idealized exponential estuary. As a major product of this study, maps of the spatial distribution of the effective diahaline diffusivities are shown for the model estuary.