bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Snow Properties on Ka- and Ku-band Winter and Melt Season Microwave Signatures of Arctic Sea Ice
Authors: Nandan Vishnu , Willatt Rosemary , Stroeve Julienne , Mallett Robbie ,   MOSAiC - Team ICE and RS
Published: March 2021

We present the baseline and detailed assessment of Ka- and Ku-band microwave signatures of winter (Legs 1 and 2) and melt season (Leg 4) snow-covered sea ice, acquired during the 2019-2020 MOSAiC International Arctic Drift Expedition. The microwave signatures were acquired using a surface-based, fully-polarimetric, Ku- and Ka-band radar (KuKa radar), acquired coincident with in situ meteorological and snow/sea ice geophysical property measurements. The KuKa radar mimicked the center frequencies of presently operational Ku- and Ka-band satellite radar altimeter and scatterometer missions.

Preliminary observations, supported by microwave backscatter modeling indicates dominant Ka-band snow surface scattering and its strong sensitivity due to snow surface roughness and its changes, induced by snow accumulation, wind-driven redistribution/erosion. For Ku-band, winter backscatter signatures originate from the snow/sea ice interface. We also showcase the winter backscatter sensitivity through its impact during the November 2019 warm storm.  During advanced melt, the Ka- and Ku-band signatures demonstrates sensitivity to snow surface melt/refreeze diurnal cycling, caused by fluctuations in liquid water content. During the melt cycle, scattering loss and absorption dominated both frequencies, while refrozen snow surface scattering dominated the refreeze cycle (observed during morning and evening scans). 

Observations from the KuKa radar will in turn provide critical understanding of snow/sea ice geophysical processes over the annual cycle, that will improve the accuracy of satellite-based retrievals of snow/sea ice critical state variables such as snow depth, sea ice thickness,  freeze-up and melt-onset timings etc, from operational and forthcoming missions such as AltiKa, CryoSat-2, Sentinel-3, ScatSat-1, CRISTAL etc. 
Chemical Enhanced Oil Recovery and Nanotechnology: Effects of Silica-Based Nanofluids on Low-Salinity Water Flooding and Enhanced Oil Recovery Processes in Oil-Wet and Water-Wet Reservoirs
Authors: Darnault Christophe , Phibbs Bruce , McCarroll Casey , Blanton Brightin
Published: March 2021

Advances in the field of nanoscience and nanotechnology have resulted in the development of engineered nanoparticles, with unique physico-chemical properties, and their applications to all the sectors of industry, including the petroleum industry. This presentation will discuss several advances and applications of silica-based nanofluids in chemical enhanced oil recovery (EOR) processes related to interfacial phenomena in multiphase systems and physics of multiphase flow in porous media, and in particular the oil recovery characteristics resulting from nanofluids based low-salinity water flooding and chemical EOR processes. Laboratory experiments were carried out using homogeneous sandpack columns simulating oil-wet and water-wet reservoirs. To simulate oil-wet reservoirs, the sandpack columns were saturated with a light crude oil (West Texas Intermediate) at first. While in the case of the simulated water-wet reservoirs, these reservoirs were made by saturating the sandpack columns initially with a 1.0 wt% brine (NaCl) and then followed by an injection of the light crude oil. The subsequent oil-saturated (oil-wet system) and oil-brine mixture (water-wet system) within the sandpack columns were then subject to water flooding (non-sequenced recovery) or EOR processes (sequenced recovery) utilizing brine and/or surfactant as controls as well as low (0.01 wt%) and high (0.1 wt%) silica-based nanofluids. When compared with the high concentration of silica-based nanofluid, the low silica-based nanofluid concentration produced low fractional and cumulative oil recovery results in the water flooding process of oil recovery for both oil-wet and water-wet reservoir systems; however, the low silica-based nanofluid concentration was found to be the most effective with EOR process for both oil-wet and water-wet reservoir systems. Our findings permit to choose optimal concentrations of silica nanoparticles to be employed for either water flooding or EOR processes in order to increase the oil extraction efficiency.
Analyzing the Kinetic Energy budget of submesoscale-permitting ensemble simulations
Authors: Jamet Quentin , Dewar William K. , Penduff Thierry , Le Sommer Julien , Leroux Stephanie , Molines Jean-Marc , Gula Jonathan
Published: March 2021

Ensemble simulations are becoming more and more popular in oceanography. Among other advantages, this modeling strategy elevates the number of dimensions available to apply statistics, and then offer new opportunities to disentangle small scale ocean turbulence from the larger scale (ensemble mean) flow, as well as their interactions. In such a framework, ocean turbulence is usually defined as the ensemble spread, reflecting the intrinsic variability that spontaneously emerges from the ocean, while the larger scale flow is defined as the ensemble mean, and whose variability is controlled by the forcing. Here, we aim at leveraging results of recently produced, submesoscale-permitting (1/60o) ensemble simulations of a forced ocean model configuration of the western Mediterranean Sea (MEDWEST60, 20 members) to diagnose the role played by ocean turbulence in the Kinetic Energy (KE) budget of these simulations. We develop for this purpose offline tools to compute such budget based on the NEMO modeling platform, which we aim at presenting.

These offline tools are part of the CDFTOOLS, a FORTRAN based package developed to export the NEMO code into an offline version of it for post-processing. Our contributions have been to include the momentum budget of the code into this package, on which kinetic energy builds upon. We first evaluate the accuracy of these offline computations against online estimates over a short period of time. At the model time step, this accuracy reaches  up to 10-3 -10-4 for time rate of change, advection and pressure work, and 10-1 for vertical dissipation. The surface pressure correction associated with the time-splitting scheme has proven difficult to implement offline, due to 1/ sub-domain boundaries instabilities in the computation of the barotropic mode, and 2/ replication of the interpolation scheme used in NEMO for atmospheric forcing fields (atmospheric surface pressure, evaporation, precipitations, runoff). The use of one hour model outputs is found to degrade the accuracy of the offline estimates by up to one order of magnitude locally. We then present and discuss preliminary applications of these diagnostics to the MEDWEST60 ensemble simulation model outputs (hourly averages).
Evidence of secondary organic aerosols formation by non-methane hydrocarbons condensation in cold Pyro-cumulonimbus (pyroCb) outflows
Authors: Benedict Katherine , Gorkowski Kyle , Lee James , Simpson Isobel , Barletta Barbara , Blake Donald , Diskin Glenn , Katich Joseph , Schwarz Joshua , Reisner Jon , Dubey Manvendra
Published: March 2021

Particle and trace gas emissions can undergo rapid changes in the atmosphere as a result of evaporation, condensation, and coagulation processes that are driven by dynamics and photochemistry.  Here we analyze the fate of non-methane hydrocarbons (NMHCs) gases emitted by intense fires associated with pyroCbs towers that rise and cool rapidly and undergo relatively little dilution as they loft smoke into the upper troposphere and lower stratosphere.  We use airborne observations of plumes from the Williams Flats Fire over the continental United States taken during 2019 FIREX-AQ campaign.  Trace gas data from both fresh boundary smoke and PyroCb-lofted smoke from this fire are compared to that from smoke plumes that stayed at lower altitudes to constrain the roles of condensation, cloud processing and photochemistry in the outflow of pyroCbs.  In the pyroCb outflows we observe lower CO normalized NMHCs mixing ratios with low vapor pressure compared to the boundary layer samples while for high vapor pressure compounds there is little difference between the CO normalized NMHC mixing ratios observed in the different fresh smoke plumes.  Associated with this decrease in condensable NMHCs we find an increase in particle concentrations, specifically at large sizes (~350nm). These multiple observational facts are used to estimate the secondary organic aerosol production by NMHC condensation in pyroCb.  Further analysis of FIREX-AQ data will be used to elucidate the roles of solubility and photochemistry on SOA formation in pyroCbs. These FIREX-AQ results will be used to inform cloud resolving large eddy simulation (LES, HIGRAD) to examine deep convective fire impacts on long range smoke impacts on climate and air quality.
Rapid 3D geological modeling to assess and visualize uncertainties in a web application
Authors: Pflieger Daniel , de la Varga Hormazabal Miguel , Virgo Simon , von Harten Jan , Wellmann Florian
Published: March 2021

Three dimensional modeling is a rapidly developing field in geological scientific and commercial applications. The combination of modeling and uncertainty analysis aides in understanding and quantitatively assessing complex subsurface structures. In recent years, many methods have been developed to facilitate this combined analysis, usually either through an extension of existing desktop applications or by making use of Jupyter notebooks as frontends. We evaluate here if modern web browser technology, linked to high-performance cloud services, can also be used for these types of analyses.

For this purpose, we developed a web application as proof-of-concept with the aim to visualize three dimensional geological models provided by a server. The implementation enables the modification of input parameters with assigned probability distributions. This step enables the generation of randomized realizations of models and the quantification and visualization of propagated uncertainties. The software is implemented using HTML Web Components on the client side and a Python server, providing a RESTful API to the open source geological modeling tool “GemPy”. Encapsulating the main components in custom elements, in combination with a minimalistic state management approach and a template parser, allows for high modularity. This enables rapid extendibility of the functionality of the components depending on the user’s needs and an easy integration into existing web platforms.

Our implementation shows that it is possible to extend and simplify modeling processes by creating an expandable web-based platform for probabilistic modeling, with the aim to increase the usability and to facilitate access to this functionality for a wide range of scientific analyses. The ability to compute models rapidly and with any given device in a web browser makes it flexible to use, and more accessible to a broader range of users.
From Micro-level Weather Shocks to Macroeconomic Impacts
Authors: Harding Anthony
Published: March 2021

Weather matters at the local level. Microeconomic climate econometric analyses find evidence that weather has localized effects on labor supply, agricultural yields, mortality rates, and other socio-economic measures. However, macroeconomic analyses at the national level find no evidence that weather affects macroeconomic aggregates, such as GDP or aggregate productivity in the US and other developed economies. These results present a seeming contradiction. In this paper, I develop a general equilibrium theoretical model of an economy with localized weather shocks to bridge the gap between microeconomic and macroeconomic studies. The theoretical model provides a simple, modular framework for aggregating weather shock impacts. I apply the findings to an empirical setting in the US, a prime example of the contradictory findings. I first estimate the microeconomic impacts of weather on labor productivity growth across county-industry pairs in the US from 2002 to 2017. I then apply these to construct annual estimates of the impact of weather shocks across the economy on US GDP according to the theoretical framework. I construct confidence intervals using the estimated microeconomic impact uncertainty. Across the sample years, I find no evidence that the annual impacts are distinct from $0. I then deconstruct the aggregate impacts, again following the theoretical framework, to examine what generates this no-effect result. I find consistent evidence of statistically significant but heterogeneous effects across a majority of counties and industries. For example, within a given year, over two-thirds of counties are consistently and significantly impacted by their local weather. This effect is positive for some counties and negative for others. I show that it is the aggregation of these heterogeneous impacts across the spatial distribution and industrial composition of the economy that masks the impact of weather. This finding highlights the importance of understanding micro-level economic impacts and changes in the composition of economic activity for projections of future macroeconomic climate change impacts.
Historical Structure From Motion (HSfM): Automated production of high-resolution DEMs from historical aerial photography for long-term geodetic change analysis
Authors: Knuth Friedrich , Shean David , Bhushan Shashank
Published: March 2021

Mountain glaciers have lost significant mass over the past century in response to a globally warming climate. However, on interannual to decadal time scales, many glaciers in Western North America show periods of both advance and retreat. To better understand these systems and their sensitivity to climate forcing, we are generating regional records of glacier surface elevation change from scanned historical film photographs acquired between the 1950s to 1990s. Our results will help constrain projections of future glacier change under different climate scenarios, as well as impacts on downstream water resources and geohazard risk.

Historical image pre-processing and manual ground control point (GCP) selection are time-intensive bottlenecks during traditional SfM processing workflows. We developed an automated photogrammetry processing pipeline (HSfM) to systematically process large archives of vertical aerial film photographs and generate sub-meter resolution digital elevation models (DEMs), without manual GCP selection. We present several case studies for glaciers in the Western North America using photos from the USGS North American Glacier Aerial Photography (NAGAP) and Earth Explorer Aerial Photography Single Frame archives, which differ in terms of available image overlap, survey area extent, and terrain characteristics. Absolute vertical accuracy of <0.5-1.0 m is achieved through iterative closest point (ICP) co-registration over stable bare-ground surfaces between the historical DEMs and modern high-resolution satellite or lidar reference DEMs. We demonstrate the potential for these new DEM records to quantify geodetic glacier mass balance and geomorphological change including moraine deposition, moraine degradation, and sediment redistribution in proglacial areas.
The impact of using bias-corrected precipitation in estimating extreme discharge: A study over the Italian Territory
Authors: García-Valdecasas Ojeda Matilde , Coppola Erika , Di Sante Fabio , Raffaele Francesca , Nogherotto Rita , Giorgi Filippo
Published: March 2021

A common way to study the impact of climate change on water resources is through hydrological models fed by precipitation from global or regional climate models (GCMs and RCMs, respectively). However, precipitation from climate models is usually affected by systematical biases that may produce inadequate streamflow estimations. For this reason, users find it necessary to apply some bias-corrected technique to reduce errors in precipitation before its use in hydrological simulations. Among the different methods, quantile mapping (QM) is a widely used method as it has shown satisfactory results for historical conditions.

In recent years, several studies have investigated the QM method, with a focus on mean precipitations. However, it remains quite uncertain how bias-corrected precipitation modifies river discharges, particularly the extreme discharges on a sub-daily timescale. In this framework, this study aims to quantify differences between simulated river discharges using corrected and uncorrected precipitation to feed a hydrological model in the context of flood hazard assessment in Italy.

To adequately estimate flood events, high spatiotemporal resolution data are required. Therefore, sub-daily precipitation outputs from the ICTP RegCM Regional Climate Model driven by the HadGEM2-ES model at 12 km were contemplated in this study. Precipitation outputs for the period 1976-2100 were bias-corrected concerning the observations from GRIPHO, which is a high-resolution observational product. Then, bias-corrected and uncorrected precipitations were used to feed the CETEMPS Hydrological Model (CHyM) completing thus, a set of hydrological simulations covering the entire Italian Territory, in both present-day and future conditions. Analyses focused on the comparison between simulated and observed discharges for present-day conditions, but also on the comparison between corrected and uncorrected values ​​in the future.

The results of this study could provide valuable information on whether the use of the QM method is appropriate for studying extreme discharges on a sub-daily scale, an essential issue for assessing the impacts of climate change on extreme hydrological events.

Keywords: flood hazard assessment, quantile delta mapping, CHyM model, RegCM model, Italy

Acknowledgments: The research reported in this work was supported by OGS and CINECA under HPC-TRES program award number 2020-02.
Natural disturbances and protection forests: at the cutting edge of remote sensing technologies for a rapid assessment of a stand protective function
Authors: Lingua Emanuele , Marchi Niccolò , Bettella Francesco , Costa Maximiliano , Pirotti Francesco , Piras Marco , Garbarino Matteo , Morresi Donato , Marzano Raffaella , Berger Frédéric
Published: March 2021

Protection forests can be severely affected by natural disturbances, whose consequences could greatly alter the fundamental ecosystem services they are providing. Assessing and monitoring the status of the protective function, particularly within disturbed stands, is therefore of vital importance, with timing being a critical issue. Remote sensing technologies (e.g. satellite images, LiDAR, UAV) are nowadays thoroughly available and can be usefully applied in order to quantify and monitor the protective role of Alpine forests, especially after abrupt changes in their cover and structure following the occurrence of a disturbance event. In this contribution, after a brief introduction on these technologies and their potential contribution to protection forest management, some specific case studies will be presented. In particular, we will focus on case studies involving protection forests affected by windthrows (the post-Vaia situation in the Eastern Italian Alps; Lidar and UAV surveys) and by forest fires in the Western Italian Alps (Fall 2017 fires; Sentinel-2 Images).
Resources for teachers on the “Ocean and Cryosphere in a Changing Climate”
Authors: Klein Simon , Guilyardi Eric , Sadadou Djian , Tricoire Mathilde , Wilgenbus David
Published: March 2021

The essential role of education in addressing the causes and consequences of anthropogenic climate change is increasingly being recognised at an international level. The Office for Climate Education (OCE) develops educational resources and proposes professional development opportunities to support teachers, worldwide, to mainstream climate change education. Drawing upon the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, the OCE has produced a set of educational resources that cover the scientific and societal dimensions, at local and global levels, while developing students’ reasoning abilities and guiding them to take action (mitigation and/or adaptation) in their schools or communities. These resources include:

1. Ready-to-use teacher handbook that (i) target students from the last years of primary school to the end of lower-secondary school (aged 9 to 15), (ii) include scientific and pedagogical overviews, lesson plans, activities and worksheets, (iii) are interdisciplinary, covering topics in the natural sciences, social sciences, arts and physical education, (iv) promote active pedagogies: inquiry-based science education, role-play, debate, projectbased learning.

2. A Summary for teachers of the IPCC Special Report, presented together with a selection of related activities and exercises that can be implemented in the classroom. 

3. A set of 10 videos where experts speak about a specific issue related to the ocean or the cryosphere, in the context of climate change.

4. A set of 4 multimedia activities offering students the possibility of working interactively in different topics related to climate change.

5. A set of 3 resources for teacher trainers, offering turnkey training protocols on the topics of climate change, ocean and cryosphere.
PANDA, the French analytical platform dedicated to ice core
Authors: Darfeuil Sophie , Ginot Patrick , Savarino Joel , Caillon Nicolas , Faïn Xavier , Teste Gregory , Landais Amaelle , Fourré Elise , Minster Bénédicte , Prié Frédéric
Published: March 2021

Since 2018, under the impetus of the IGE (Grenoble) and the LSCE (Saclay) and the common interest of the "Carottes de Glace France" consortium, an analytical platform dedicated to glacier archives was created to meet the growing analytical needs requested by projects involving French partners (Ice Memory, EAIIST, BE-OI ...) and international collaborations with a ten-year vision. Within this framework 5 modules have been developed between the IGE and the LSCE. 3 modules are installed at the IGE, including a CHEMISTRY module which includes a large number of instruments coupled to the CFA (Continuous Flow Analysis) system, allowing high-resolution multi tracer analysis on a single ice stick (water isotopes, dust, conductivity, colorimetry, black carbon, trace metals and gas) as well as several auto-samplers for discrete analyses (major ions, organic species, trace metals, sugars ...). The GAS module is shared between continuous analyses on the CFA system (laser spectrometry CH4/CO) and discrete analyses (Gas chromatography CH4/CO2). The ISOTOPY module allows the analysis of nitrogen (N), sulfur (S) and oxygen (O) isotopes. At the LSCE, the WATER ISOTOPY module allows continuous (Picarro coupled to a CFA line equipped with conductivity cells and auto-sampler) or discrete (Picarro or mass spectrometer) analyses for δD, δ18O and δ17O in water. The AIR ISOTOPY module completes the platform for analyses by mass spectrometry of δ15N of N2, the triple isotopic composition of O2 and noble gases isotopes (36/38/40 Ar; 82/84/86 Kr; 129-132 Xe). An overview of the capacity and performance of the platform will be presented.
Investigation of a multiphysics joint inversion framework
Authors: Molodtsov Dmitry , Kiyan Duygu , Bean Christopher
Published: March 2021

We present a 3-D multiphysics joint inversion framework that in a certain sense is a trade-off between “simultaneous” and “cooperative” approaches to data integration. Using a variable splitting approach, inverse problems are solved by individual inverse solvers, on individual grids, while coupling combined with interpolation is implemented separately. Up to date, first-arrival seismic tomography, gravity and magnetotelluric inverse problems are included in this framework. Magnetotelluric inversion uses the NLCG method implemented in the ModEM code (Kelbert et al., 2014). Seismic tomography is based on the Gauss-Newton method with a finite-difference eikonal solver and posterior ray tracing. Gravity inversion uses the conjugate gradient method with wavelet compression of the sensitivity matrix. Structure coupling is based on mixed-norm regularization inducing joint sparsity between the models. Among particular functionals that were studied, following numerical experiments, joint total variation and joint minimum support have proved to be the most efficient options. In the numerical experiments, we invert synthetics simulating regional datasets observed in Ireland.
Sensitivity of organic carbon fluxes from Arctic coastal erosion to climate change
Authors: Nielsen David Marcolino , Pieper Patrick , Brovkin Victor , Overduin Paul , Ilyina Tatiana , Baehr Johanna , Dobrynin Mikhail
Published: March 2021

When unprotected by sea-ice and exposed to the warm air and ocean waves, the Arctic coast erodes and releases organic carbon from permafrost to the surrounding ocean and atmosphere. This release is estimated to deliver similar amounts of organic carbon to the Arctic Ocean as all Arctic rivers combined, at the present-day climate. Depending on the degradation pathway of the eroded material, the erosion of the Arctic coast could represent a positive feedback loop in the climate system, to an extent still unknown. In addition, the organic carbon flux from Arctic coastal erosion is expected to increase in the future, mainly due to surface warming and sea-ice loss. In this work, we aim at addressing the following questions: How is Arctic coastal erosion projected to change in the future? How sensitive is Arctic coastal erosion to climate change?

To address these questions, we use a 10-member ensemble of climate change simulations performed with the Max Planck Institute Earth System Model (MPI-ESM) for the Coupled Model Intercomparison Project phase 6 (CMIP6) to make projections of coastal erosion at a pan-Arctic scale. We use a semi-empirical approach to model Arctic coastal erosion, assuming a linear contribution of its thermal and mechanical drivers. The pan-Arctic carbon release due to coastal erosion is projected to increase from 6.9 ± 5.4 TgC/year (mean estimate ± two standard deviations from the distribution of uncertainties) during the historical period (mean over 1850 -1950) to between 13.1 ± 6.7 TgC/year and 17.2 ± 8.2 TgC/year in the period 2081-2100 following an intermediate (SSP2.4-5) and a high-end (SSP5.8-5) climate change scenario, respectively. The sensitivity of the organic carbon release from Arctic coastal erosion to climate warming is estimated to range from 1.52 TgC/year/K to 2.79 TgC/year/K depending on the scenario. Our results present the first projections of Arctic coastal erosion, combining observations and Earth system model (ESM) simulations. This allows us to make first-order estimates of sensitivity and feedback magnitudes between Arctic coastal erosion and climate change, which can lay out pathways for future coupled ESM simulations.

 
A network model for ponding on sea ice
Authors: Coughlan Michael
Published: March 2021

I present a physically-based network model for systems of ponds which accounts for both the individual and collective behaviour of ponds, and allows us to investigate the behaviour of both. Each pond initially occupies a distinct catchment basin and evolves according to a mass-conserving differential equation representing the melting dynamics for bare and water-covered ice. Ponds can later connect together to form a network with fluxes of water between catchment areas, constrained by the ice topography and pond water levels. 

I use the model to explore how the evolution of pond area and hence melting depends on the governing parameters, and to explore how the connections between ponds develop over the melt season. Comparisons with observations are made to demonstrate the ways in which the model qualitatively replicates properties of pond systems, including fractal dimension of pond areas and two distinct regimes of pond complexity that are observed during their development cycle. The network structure, and tools from percolation theory also allows us to probe how the connectivity of pond systems affect the system at each stage of development.
Transdisciplinary Design of Adaptation Pathways in Peri-urban India: Planning for Water Needs in a Sustainable Urban Transition 
Authors: Gomes Sharlene L. , Luft Sarah , Chakraborty Shreya , Hermans Leon M. , Butsch Carsten
Published: March 2021

This research, conducted within the H2O-T2S project, is located in peri-urban areas of three cities in India: Pune, Hyderabad, Kolkata. Peri-urban areas are where the rural to urban transition is most visible. A key challenge for peri-urban areas is sustainable management of water resources. Peri-urban water resources in India are under threat from growing water demand and ineffective institutions. Interdisciplinary research of existing water-based livelihoods, household water use, and peri-urban institutions in these three regions shows that current urban transformations are unsustainable. Given the dynamic nature of peri-urban contexts, short and long-term vulnerabilities must be considered. An adaptation policy pathways approach can help peri-urban actors develop longer-term transformative plans. This study describes the design and execution of a participatory process to design context-specific pathways with peri-urban communities and governments in India.

This presentation outlines the key steps in our customized pathways approach for the peri-urban context. Due to the covid-19 pandemic, initial plans to implement these steps through a series of stakeholder workshops were replaced by remote pathways design using the Delphi method. We present a step-by-step methodology to engage peri-urban actors in the design of longer-term adaptive plans for water resources in the future. Results are presented for Hadia village (Kolkata), one of the three peri-urban case studies. It reveals the range of future normative scenarios developed for this village and a pathways schematic towards these scenarios.

Our results demonstrate the value of engaging local actors in the design of adaptive plans for peri-urban water resources. This study offers insights for ways to conduct transdisciplinary research even when face to face interactions are not feasible.
A myriad of melt inclusions: a synchrotron microtomography study of melt inclusions and vapour bubbles from Colli Albani (Italy)
Authors: Jorgenson Corin , Caricchi Luca , Stueckelberger Michael , Fevola Giovanni , Weber Gregor
Published: March 2021

Melt inclusions provide a window into the inner workings of magmatic systems. Both mineral chemistry and volatile distributions within melt inclusions can provide valuable information about the processes modulating magma ascent and preceding volcanic eruptions. Many melt inclusions host vapour bubbles which can be rich in CO2 and H2O and must be taken into consideration when assessing the volatile budget of magmatic reservoirs. These vapour bubbles can be the product of differential volumetric contraction between the melt inclusion and host phase during an eruption or indicate an excess fluid phase in the magma reservoir. Thus, determining the distribution of volatiles between melt and vapour bubbles is integral to our fundamental understanding of melt inclusions, and by extension the evolution of volatiles within magmatic systems.

A large dataset of 79 high-resolution tomographic scans of clinopyroxene and leucite phenocrysts from the Colli Albani Caldera Complex (Italy) was recently acquired at the German Electron Synchrotron (DESY). These tomograms allow us to quantify the volume of melt inclusions and associated vapour bubble both glassy and microcrystalline melt inclusions. Notably, in the glassy melt inclusions the vapour bubbles exist either as a single large vapour bubble in the middle of the melt inclusion or as several smaller vapour bubbles distributed around the edge of the melt inclusion. These two types of melt inclusions can coexist within a single crystal. We suggest that the occurrence of these rim- bubbles is caused by one of two exsolution pathways, either pre-entrapment and bubble migration or post entrapment with preferential exsolution at the rims. By combining the analysis of hundreds of melt inclusions with the chemistry of the host phase we aim to unveil magma ascent rates and distribution of excess fluids within the magmatic system of Colli Albani, which produced several mafic-alkaline large volume ignimbrites.
Exploring microphysical properties of marine boundary layer clouds through network analysis
Authors: Ricard Lucile , Nenes Athanasios , Runge Jakob , Georgakaki Paraskevi
Published: March 2021

Aerosol-cloud interactions remain the largest uncertainty in assessments of anthropogenic climate forcing, while the complexity of these interactions require methods that enable abstractions and simplifications that allow their improved treatment in climate models. Marine boundary layer clouds are an important component of the climate system as their large albedo and spatial coverage strongly affect the planetary radiative balance. High resolution simulations of clouds provide an unprecedented understanding of the structure and behavior of these clouds in the marine atmosphere, but the amount of data is often too large and complex to be useful in climate simulations. Data reduction and inference methods provide a way that to reduce the complexity and dimensionality of datasets generated from high-resolution Large Eddy Simulations.

In this study we use network analysis, (the δ-Maps method) to study the complex interaction between liquid water, droplet number and vertical velocity in Large Eddy Simulations of Marine Boundary Layer clouds. δ-Maps identifies domains that are spatially contiguous and possibly overlapping and characterizes their connections and temporal interactions. The objective is to better understand microphysical properties of marine boundary layer clouds, and how they are impacted by the variability in aerosols. Here we will capture the dynamical structure of the cloud fields predicted by the MIMICA Large Eddy Simulation (LES) model. The networks inferred from the different simulation fields are compared between them (intra-comparisons) using perturbations in initial conditions and aerosol, using a set of four metrics. The networks are then evaluated for their differences, quantifying how much variability is inherent in the LES simulations versus the robust changes induced by the aerosol fields. 
Application of Deep Learning for Planar 3D Hydraulic Fracturing Simulation
Authors: Dochkina Victoria , Perepechkina Ilia , Zavialova Natalia , Negodiaev Sergei
Published: March 2021

    Nowadays, none of widely used hydraulic fracturing simulators can simultaneously provide high calculation speed and sufficient physical reliability, which is crucial in engineering problems. Hence, an optimization of hydraulic fracturing simulation in terms of speed and accuracy is needed. It is possible to create a tool that will simultaneously solve the above-mentioned problems using Machine Learning methods. In that case, the simulation will have an accuracy close to the Planar3D model and almost instantaneous speed of calculation. The development of such a tool will simplify a selection of optimal injection parameters.
    This paper presents a Neural Network that approximates a planar three-dimensional hydraulic fracturing model. A feature of the proposed approximator is that it predicts the evolution of two-dimensional fracture aperture field. This is a key difference of this model from other approximators that predict well-defined parameters of the fracture geometry, such as half-length, height, etc. The availability of complete fracture geometry information allows highly accurate estimation of production and possible complications during hydraulic fracturing.
    The paper presents an ability of creating a Neural Network that will cover a wide range of production problems: from express simulation and optimization to accurate and physically reliable modeling.
First solar electron events observed by EPD aboard Solar Orbiter
Authors: Gómez-Herrero Raúl , Pacheco Daniel , Kollhoff Alexander , Espinosa Lara Francisco , Freiherr von Forstner Johan L. , Dresing Nina , Lario David , Balmaceda Laura , Krupar Vratislav , Malandraki Olga E. , Aran Angels , Bucik Radoslav , Klassen Andreas , Klein Karl-Ludwig , Cernuda Ignacio , Eldrum Sandra , Reid Hamish , Mitchell John G. , Mason Glenn M. , Ho George C. ,   Solar Orbiter EPD/RPW/MAG/SWA Teams
Published: March 2021

The first solar electron events detected by Solar Orbiter were observed by the Energetic Particle Detector (EPD) suite during July 11-23, 2020, when the spacecraft was at heliocentric distances between 0.61 and 0.69 au. We combined EPD electron observations from 4 keV to the relativistic range (few MeV), radio dynamic spectra and extreme ultraviolet (EUV) observations from multiple spacecraft in order to identify the solar origin of these electron events. Electron anisotropies and timing as well as the plasma and magnetic field environment were evaluated to characterize the interplanetary transport conditions. We found that all the electron events were clearly associated with type III radio bursts. EUV jets were also found in association with all of them except one. A diversity of time profiles and pitch-angle distributions (ranging from almost isotropic to beam-like) was observed. These observations indicate that different source locations and different magnetic connectivity and transport conditions were likely involved. The broad spectral range covered by EPD with excellent energy resolution and the high time cadence ensure that future observations close to the Sun will contribute to the understanding of the acceleration, release, and transport processes of energetic particles. EPD observations will play a key role in the identification of the sources of impulsive events and the links between the near-relativistic electrons and the ion populations enriched in 3He and heavy ions

 
Recent development of a supermodel - an interactive multi-model ensemble
Authors: Wang Shuo , Counillon Francois , Koseki Shunya , Keenlyside Noel , Gupta Alok Kumar , Shen Maolin
Published: March 2021

An interactive multi-model ensemble (named as supermodel) based on three state-of-the-art earth system models (i.e., NorESM, MPIESM and CESM) is developed. The models are synchronized every month by data assimilation. The data assimilation method used is the Ensemble Optimal Interpolation (EnOI) scheme, for which the covariance matrix is constructed from a historical ensemble. The assimilated data is a weighted combination of the monthly output sea surface temperature (SST) of these individual models, but the full ocean state is constrained by the covariance matrix. The synchronization of the models during the model simulation makes this approach different from the traditional multi-model ensemble approach in which model outputs are combined a-posteriori.

We compare the different approaches to estimate the supermodel weights: equal weights, spatially varying weights based on the minimisation of the bias. The performance of these supermodels is compared to that of the individual models, and multi-model ensemble for the period 1980 to 2006. SST synchronisation is achieved in most oceans and in dynamical regimes such as ENSO. The supermodel with spatially varying weights overperforms the supermodel with equal weights. It reduces the SST bias by over 30% compare to the multi-model ensemble. The temporal variability of the supermodel is slightly on the low side but improved compared to the multi-model ensemble. The simulations are being extended to 2100 to assess the simulation of climate variability and climate change. Performing prediction experiments with the supermodel is the main perspective in the next step.  
Boreal Vegetation and Soil Carbon Dynamics in Response to a Changing Climate and Soil Variables
Authors: Galbraith John , Krasilnikov Pavel , Rumpel Cornelia
Published: March 2021

Many soils in the Boreal forest regions of the Arctic store very large amounts of carbon in the active layer above permafrost, and store significant amounts of carbon within the permafrost. Soils that are well drained, high in rock fragments, shallow to rock or rubble, or covered with ice are exceptions. No other region on Earth stores more carbon on average than the Arctic regions, especially in wetlands. However, changes in vegetation and soil are expected under warming climates. Research questions have arisen about future changes in vegetation and net carbon flux as soil and air temperatures climb, as precipitation amount and type changes, and as the growing season lengthens. A review of recent literature will be conducted to look at effects of vegetation change and annual carbon dynamics in Boreal forest and wetland soils under warming climates. Environmental variables such as soil temperature, hydrology, microbial and higher plant growth, digestibility of young and old carbon, fire, location zone, extent and type of permafrost thaw slow vs sudden collapse), and N and P nutrient balances will affect carbon stocks in addition to changing climate.
Comparison of polar stratospheric cloud detection and composition as observed by ground-based lidar and CALIOP at Dome C.
Authors: Snels Marcel , Colao Francesco , Cairo Francesco , Shuli Ilir , Scoccione Andrea , De Muro Mauro , Pitts Michael , Poole Lamont , Di Liberto Luca
Published: March 2021

Polar stratospheric clouds have been observed at Dome C by a ground-based lidar from 2014 up to the present, possibly in coincidence with nearby overpasses of the CALIPSO satellite, with the CALIOP lidar on board.

A thorough study has been made in terms of detection efficiency and composition classification of near coincident lidar observations, with the goal to identify the main biases between the two lidars.

When comparing ground-based lidar observations with nearby CALIOP overpasses, several biases might occur, due to the distance between ground-based lidar and nearest overpass, observation geometry and integration times and different algorithms used for data analysis.

The bias resulting from different data analysis has been reduced by applying an algorithm for PSC detection and composition classification to the ground-based data which is very similar to the V2 algorithm used for CALIOP.

By comparing 5 years of PSC observations at Dome C, considering both detection efficiency and composition of the observed PSCs, the impact of all biases will be discussed and possibly quantified. 
An Analysis of the Importance of a Fully-Coupled Atmosphere and Land-Surface When Considering the Impact of Multi-Scale Land Spatial Heterogeneity on Cloud Development
Authors: Simon Jason , Waterman Tyler , Hay-Chapman Finley , Dirmeyer Paul , Bragg Andrew , Chaney Nathaniel
Published: March 2021

Land-surface heterogeneity is known to play an important role in land-surface hydrology, which drives the bottom boundary condition for atmospheric models in numerical weather prediction (NWP) applications. However, the ultimate impact of land-surface heterogeneity on atmospheric boundary layer (ABL) development is still an open problem with implications for sub-grid scale (SGS) parameterizations for both NWP and climate modeling. Large-eddy simulation (LES) is often used to study the effects of land-surface heterogeneity on ABL development, most typically via specified surface fields which are not influenced by the atmosphere (i.e. semi-coupled). Heterogeneous land surfaces have been seen in previous studies to have a significant influence on ABL dynamics, particularly cloud production, in certain cases when semi-coupled to the atmosphere.

Here we use the Weather Research and Forecasting (WRF) model as an LES with both semi-coupled and fully-coupled land surfaces to investigate the impact of two-way coupling on the interaction between heterogeneous land surfaces and daytime ABLs. For semi-coupled simulations, the HydroBlocks land-surface model is run offline, driven by 4-km NLDAS-2 meteorology with Stage-IV radar rainfall data, and then used to specify the bottom boundary in WRF. The WRF-Hydro model is used for cases where the land surface is fully coupled to the WRF model. Both land-surface models use the Noah-MP model as their underlying physics package and add both subsurface and overland flow routing. The WRF model uses a 100-m horizontal resolution, and the land-surface models use high resolution (30 m) datasets that were upscaled to match the LES resolution for elevation, landcover, and soil type using NED, NLCD, and POLARIS respectively. These LES experiments are performed over the ARM Southern Great Plains Site atmospheric observatory in Oklahoma during the Summer of 2017 with a grid size of 100 km x 100 km to imitate a single cell in a modern climate model. The impact of land-surface heterogeneity on the atmosphere is evaluated by comparing simulations using the fully heterogeneous land surfaces with simulations where the land surface is homogenized at each timestep, taking a domain-wide spatial mean value at every grid cell. Results are evaluated primarily by the differences in the development of clouds and evolution of turbulent kinetic energy in the ABL.
River discharge variability in the rock record? Disentangling the relative role of flow variability and morphodynamic hierarchies on bedform preservation
Authors: Lyster Sinead , Whittaker Alexander , Hajek Elizabeth , Ganti Vamsi , Allison Peter
Published: March 2021

River discharge variability is a fundamental control on fluvial morphodynamics and, in principle, stratigraphic architecture. The ability to quantitatively constrain discharge variability from fluvial stratigraphy would newly enable us to reconstruct instantaneous or interannual responses of rivers to climatic perturbation in the geologic past. However, the extent to which we can extract quantitative information about discharge variability from fluvial stratigraphy is currently unknown. Recent experimental work indicates that preserved cross-set geometries can potentially be used to inform formative flow conditions and durations. However, to date, this has not been tested on field examples of ancient fluvial systems. Here we use detailed measurements of cross-sets to assess bedform kinematics and formative flow conditions in fluvial strata of three Late Cretaceous geologic formations: the Blackhawk Formation, Castlegate Sandstone, and Ferron Sandstone, which crop out in central Utah, USA.

Unanimously low coefficients of variation (CV) in preserved cross-set heights of 0.25–0.5 are consistent with the hypothesis that CV<<0.88 arises from preservation of bedforms in disequilibrium conditions, which typically occurs during rapid flood recession in a “flashy” flood hydrograph. Bedform preservation in disequilibrium conditions requires that formative flow durations are shorter than bedform turnover timescales. We reconstruct median turnover timescales of 2–3 days, with a 10–90 percentile range of ~1–10 days, which implies that formative flow durations were of order hours to a few days. These durations are consistent with storm-related flood durations in perennial discharge regimes, as opposed to the more sustained flood durations that are typical of subtropical/monsoonal climate regimes. However, it is also possible that this same CV signature (CV<<0.88) can be achieved simply by the presence of morphodynamic hierarchies, e.g. concurrently migrating bedforms and bars. We explore whether it is possible to disentangle the relative role of formative flow conditions and morphodynamic hierarchies on bedform preservation using our field data, models of flood stratigraphy, and estimates of bedform preservation ratios. Moreover, we identify future steps that will further our ability to quantitatively extract formative flow variability and, ultimately, discharge variability from the rock record. 