bluuebunny/crossref_metadata_2025 huggingface dataset:
Social tipping processes for sustainability: An analytical framework
Authors: Winkelmann Ricarda , Donges Jonathan F. , Smith E. Keith , Milkoreit Manjana , Eder Christina , Heitzig Jobst , Katsanidou Alexia , Wiedermann Marc , Wunderling Nico , Lenton Timothy M.
Published: March 2021

Societal transformations are necessary to address critical global challenges, such as mitigation of anthropogenic climate change and reaching UN sustainable development goals. Recently, social tipping processes have received increased attention, as they present a form of social change whereby a small change can shift a sensitive social system into a qualitatively different state due to strongly self-amplifying (mathematically positive) feedback mechanisms. Social tipping processes have been suggested as key drivers of sustainability transitions emerging in the fields of technological and energy systems, political mobilization, financial markets and sociocultural norms and behaviors.

Drawing from expert elicitation and comprehensive literature review, we develop a framework to identify and characterize social tipping processes critical to facilitating rapid social transformations. We find that social tipping processes are distinguishable from those of already more widely studied climate and ecological tipping dynamics. In particular, we identify human agency, social-institutional network structures, different spatial and temporal scales and increased complexity as key distinctive features underlying social tipping processes. Building on these characteristics, we propose a formal definition for social tipping processes and filtering criteria for those processes that could be decisive for future trajectories to global sustainability in the Anthropocene. We illustrate this definition with the European political system as an example of potential social tipping processes, highlighting the potential role of the FridaysForFuture movement. Accordingly, this analytical framework for social tipping processes can be utilized to illuminate mechanisms for necessary transformative climate change mitigation policies and actions. 
Climate Science and Climate Change Across the Curricula – Seizing Opportunities
Authors: Holzer Margaret
Published: March 2021

Challenges abound as our Earth warms, seas rise, and weather extremes become more and more common. Solutions to these challenges requires the collective knowledge of many along with transdisciplinary approaches, resulting in unique, creative, and comprehensive solutions.  In addition, these challenges come in many spatial and temporal sizes, and therefore solutions are needed at local, regional, global levels organized by small scale and larger scale groups. School systems can be a hub of ingenuity when it comes to designing and implementing solutions if guided by a clear pathway. Some states in the United States of America have adopted standards for learning that include climate science and climate change across all subject areas. In these states the vision for standards implementation parallels a vision for meeting the local and regional challenges of climate change. This presentation will outline the new roles afforded schools in our collective effort to reverse climate change and reduce its impact along the way.
Radiogenic Isotope Signatures of Holocene Sediments from Kane Basin: Linkage with the Re-opening and Evolution of Nares Strait
Authors: Madaj Lina , Lucassen Friedrich , Hillaire-Marcel Claude , Kasemann Simone A.
Published: March 2021

The re-opening of the Arctic Ocean-Baffin Bay gateway through Nares Strait, following the Last Glacial Maximum, has been partly documented, discussed and revised in the past decades. The Nares Strait opening has led to the inception of the modern fast circulation pattern carrying low-salinity Arctic water towards Baffin Bay and further towards the Labrador Sea. This low-salinity water impacts thermohaline conditions in the North Atlantic, thus the Atlantic Meridional Overturning Circulation. Available land-based and marine records set the complete opening between 9 and 7.5 ka BP [1-2], although the precise timing and intensification of the southward flowing currents is still open to debate. A recent study of a marine deglacial sedimentary record from Kane Basin, central Nares Strait, adds information about subsequent paleoceanographic conditions in this widened sector of the strait and proposed the complete opening at ~8.3 ka BP [3].

We present complementary radiogenic strontium, neodymium and lead isotope data of the siliciclastic detrital sediment fraction of this very record [3] further documenting the timing and pattern of Nares Strait opening from a sediment provenance approach. The data permit to distinguish detrital material from northern Greenland and Ellesmere Island, transported to the core location from both sides of Nares Strait. Throughout the Holocene, the evolution of contributions of these two sources hint to the timing of the ice break-up in Kennedy Channel, north of Kane Basin, which led to the complete opening of Nares Strait [3]. The newly established gateway of material transported to the core location from the north via Kennedy Channel is recorded by increased contribution of northern Ellesmere Island detrital sediment input. This shift from a Greenland (Inglefield Land) dominated sediment input to a northern Ellesmere Island dominated sediment input supports the hypothesis of the newly proposed timing of the complete opening of Nares Strait at 8.3 ka BP [3] and highlights a progressive trend towards modern-like conditions, reached at about 4 ka BP.

References:

[1] England (1999) Quaternary Science Reviews, 18(3), 421–456. [2] Jennings et al. (2011) Oceanography, 24(3), 26-41. [3] Georgiadis et al. (2018) Climate of the Past, 14 (12), 1991-2010.
Sustainable Deltas in the Anthropocene
Authors: Nicholls Robert , Adger Neil , Hutton Craig , Hanson Susan , Lázár Attila , Vincent Katharine , Allan Andrew , Tompkins Emma , Arto Iñaki , Rahman Munsur , Hazra Sugata , Codjoe Sam , Darby Stephen
Published: March 2021

Populous deltas exemplify many of the diverse social and environmental changes and challenges that are emerging across the planet during the Anthropocene. Loss of relative elevation due to relative sea-level rise (combining climate and subsidence effects) is one major threat, but there are others such as catchment changes (e.g., water extraction and dam construction) which reduce water and sediment inputs. Rapid socio-economic changes within a delta (e.g., migration, urbanisation, economic transition and land use change) are also widespread and frequently add further pressures on the environmental resources  contained within delta systems. There are long histories of evolving adaptation practice at household to community level. In the long-term (i.e. 2100 and beyond), given relative sea-level rise, there are three distinct (but not necessarily mutually exclusive) policy choices for deltas: (i) retreat and progressive abandonment of the coastal zone; (ii) protection with ever-higher defences, growing pumping needs, and residual risk issues; or (iii) raise land elevation by controlled sedimentation. Building elevation is an attractive option if sufficient sediment is available, and there are now a few innovative examples that show it can be delivered to the delta surface— for example, through strategic raising of agricultural and natural areas with controlled sedimentation. One challenge is to accomplish this in a way which does not disrupt the livelihoods of the delta residents. Further is sufficient sediment available now or in the future, and what about growing urban areas where flood defence is likely to remain the norm? This raises the question about the trade-off between elevation and wealth. Many deltas cope with ‘lost elevation’ via defences: the Netherlands is most advanced in this approach, but such defences are expensive, require access to technology, and require sophisticated governance arrangements to deliver. A range of potential adaptation options at different scales and with different levels of cost will be required to sustain delta futures. This presentation examines potential adaptation options and trade-offs and delta trajectories in a range of examples including the Volta delta, Ghana, the Mahanadi delta, India and the Ganges-Brahmaputra-Meghna delta, India and Bangladesh.
Seasonal variation of microplastics ingested by copepods in Jiaozhou Bay, the Yellow Sea
Authors: Zheng Shan , Sun Xiaoxia
Published: March 2021

Microplastic (MP) contamination is a growing threat to marine biota and ecosystems. As the dominant functional group of zooplankton, copepods are at an increased risk of MP ingestion. The seasonal change in MPs in copepods and the key environmental factors influencing the retention of MPs in copepods are largely unknown. For the first time, the characteristics of MPs in copepods across four seasons were studied in Jiaozhou Bay. The abundance, shape, size, and chemical composition of MPs in copepods were investigated, and the relationships between MP/copepod and key environmental factors were analyzed. The results reveal a significant seasonal difference in the MP/copepod in Jiaozhou Bay. The MP/copepod was 0.26, 0.23, 0.14 and 0.16 in February, May, August and November, respectively. The MP/copepod was significantly higher in winter and spring than in summer, which was possibly correlated with the lower temperature in winter and spring seasons. Seawater temperature was negatively correlated with the MP/copepod value. The MP/copepod in the area near the estuary was significantly higher than inside the bay. No significant seasonal differences were detected in the characteristics of MPs in copepods in Jiaozhou Bay. The size of MPs in copepods ranged from 90 to 2485 μm, with an average of 454±376 μm. Fibers are the most risky MPs in copepods, accounting for 92% of the total. In terms of the chemical composition, a total of 20 polymers were detected from copepods in Jiaozhou Bay in four seasons. The main components were polyester and cellophane. The percentages of polyester were 29.4%, 45.5%, 41.2%, and 57.1%, and those of cellophane were 52.9%, 18.2%, 11.8%, and 28.6% in February, May, August and November, respectively. By revealing the seasonal characteristics of copepods in Jiaozhou Bay, this study provided key parameters of MPs in copepods in Jiaozhou Bay and formed an important basis for further ecological risk assessment of MPs. The chronic effects of low MP retention on copepods, the impact of fibers on copepods, and the risk assessments of MPs under different environmental conditions were recommended as the research topic for the next step to achieve an environmentally relevant risk assessment.
Global moisture transport and the role of major teleconnection patterns
Authors: Vázquez Marta , Nieto Raquel , Liberato Margarida , Gimeno Luis
Published: March 2021

The teleconnection patterns are an important feature influencing the variability of moisture transport toward the continent. This work analyses the influence of the Arctic Oscillation, Antarctic Oscillation, Pacific North America, and ENSO on the moisture transport from major oceanic and continental moisture sources in the month of higher precipitation. The Pacific North America higher influence is observed over North America with an increased contribution to the western region from the Pacific and lower over the eastern region from the Atlantic in the positive phase. The moisture transport during Arctic Oscillation events seems to be modulated by the Mediterranean Sea and North Atlantic, increasing from the Mediterranean in the positive phase and decreasing from the Atlantic. The Antarctic Oscillation shows its most relevant influence over Australia and Eastern Africa, with increased moisture contribution from eastern regions on the positive phase. Finally, ENSO events show influence in moisture transport over different areas in the world. El Niño events are associated with increased transport from the Atlantic region over western Europe and from the Pacific over North America. In South and Central America, the moisture contribution decreased over the regions closer to the equator, while the opposite occurs over southern South America. Over eastern Africa and Southern Asia, moisture inflow from the Indian Ocean seems to be affected by the pattern. The result suggests the influence of the moisture contribution on the precipitation pattern in association with main teleconnection patterns.
Convective heat transfer of water flowing in intersected rock fractures for enhanced geothermal extraction
Authors: chen Yuedu
Published: March 2021

Numerous intersected rock fractures constitute the fracture network in enhanced geothermal systems. The complicated convective heat transfer behavior in intersected fractures is critical to the heat recovery in fractured geothermal reservoirs. A series of three-dimensional intersected fracture models are constructed to perform the flow-through heat transfer simulations. The geometries effects of dead-end fractures on the heat transfer are evaluated in terms of intersected angles, apertures, lengths, and the connectivity. The results indicate that annular streamlines appear in the rough dead-end fracture and cause an ellipsoidal distribution of the cold front. Compared to the steady flow in plate dead-end fractures, the fluid flow formed in the rough dead-end fracture enhances the heat transfer. Both the outlet water temperature Tout and heat production Q present the largest when the intersected angle is 90°. A larger intersected angle and longer length extension of the intersected dead-end fracture, raising Tout and Q, are beneficial to the heat production, while increasing the aperture is ineffective. Solely increasing numbers of dead-end fractures poses a little increase on Tout and Q. More significant heat extraction is obtained through connecting these dead-end fractures with the main flow fracture forming the flow network.
Shallow Crustal Structure in the DehDasht Region (SW Iran) from Ambient Seismic Noise Tomography
Authors: Shakeri Nastaran , Shirzad Taghi , Ashkpour Motlagh Shobeir , Norouzi Siavash
Published: March 2021

Zagros continental collision zone (S-SW Iran) is tectonically active and extends over 1800 km contained most part of hydrocarbon reservoirs worldwide. The DehDasht region is located in the southeast of the Dezful embayment in the Zagros fold-and-thrust belt. The existence of an evaporation layer with high velocity features is the main challenge to apply classical seismic exploration in this region. However, ambient seismic noise carries valuable information about the propagation path; hence it could be a useful tool for studying crustal structure in the DehDasht region. For this purpose, we used up to 9 months of continuous data recorded by 107 stations in the area with ~16 × ~24 km2. All stations are equipped with broadband (120s) sensors recording at 100 sps. The standard ambient seismic noise processing was done as outlined by Bensen et al. (2007), and optimize empirical Green’s function (EGF) was retrieved based on the WRMS stacking method. Afterward, Rayleigh wave dispersion measurements were calculated using the FTAN approach in the period range of 0.1-5.0 s, then the inversion procedure was performed by the Fast-Marching Method with an inversion cell size of 2×2 km. Our group velocity tomographic maps show a high velocity anomaly in the Khaviz Mountain belt (west part of the study area) is generally linked to the older, consolidated bodies while two low velocity anomalies are related to the presence of fluids and or younger structures.
New methods for quantitative climate reconstructions applied to the Levant
Authors: Netzel Timon , Hense Andreas , Litt Thomas , Miebach Andrea
Published: March 2021

On his migration out of Africa, anthropological modern human had to cross the Levant, among other places. Today, there are many different climatic zones, which are particularly evident along the Jordan Valley. For example, the Dead Sea and the Sea of Galilee in Israel are reservoirs of climate proxies and reflect climate variability during the Holocene, based on pollen and plant remains in their lake sediments.

In addition to plant information, speleothems are also useful as climatic proxies. They have been studied in many caves in the Levant. From their isotopic data, conclusions can be drawn about the climate in specific periods and areas. One task is their appropriate use in terms of quantitative climate reconstruction.

Another topic is the consideration of age uncertainties in paleoclimatology and their influence on reconstruction techniques. For this purpose, it is advantageous to use mathematical formulations that are easy to implement and calculate.

Based on data from a sediment core of Sea of Galilee we will discuss and present results for the following sequence of points: the mathematical formulation of climate reconstruction using Bayesian hierarchical models, the computation of transfer function connecting proxy information with physical climate data using machine learning techniques, and the inclusion of age uncertainty based on the output from the latest BACON version.
A multi-model ensemble weighting method (ClimWIP) in ESMValTool
Authors: Lorenz Ruth , Brunner Lukas , Kalverla Peter , Smeets Stef , Camphuijsen Jaro , Andela Bouwe
Published: March 2021

Too often model evaluation has no impact on how a multi-model ensemble is analysed. It has been argued that projection and prediction uncertainties can be decreased by giving more weight to those models in multi-model ensembles that are more skillful and realistic for a specific process or application. In addition, some models in multi-model ensembles are not independent and it is not always clear how to include available initial condition ensemble members which are becoming larger in number e.g. in CMIP6.

A weighting approach has been proposed which takes into account both of these aspects (Climate model Weighting by Independence and Performance- ClimWIP) and is able to deal with included initial condition ensemble members. This approach has been shown to decrease uncertainties in multiple use cases such as projections of Arctic September sea ice, North American summer maximum temperatures, European temperature and precipitation, as well as projected global mean temperatures. Even though the basic equation to calculate a model's weight is straight forward, the user needs to make several decisions, such as which metric to use to measure performance or independence, which variables to include etc. and potential pitfalls were identified. For the actual implementation a range of points need to be considered: (1) data from different modelling centers need to be processed and compared in a consistent way, (2) the strength of the performance and independence contributions is determined through two parameters that must also be calibrated, (3) results should be provided in a form that allows backtracing to the original data and code to allow reproducability. To facilitate re-use for new applications, the method was recently implemented into the ESMValTool. We will discuss advantages and disadvantages of the method, show results from some of the use cases, explain how the implementation into ESMValTool was done and how the method can now be more easily used.
Disentangling the mechanisms of wave-convection coupling using idealized simulations in a tropical channel: wave composites of the moist static energy budget
Authors: Jung Hyunju , Knippertz Peter , Hoose Corinna , Ruckstuhl Yvonne , Redl Robert , Janjic Tijana
Published: March 2021

Recent studies found that the coupling of equatorial waves to convection is key to improving weather forecasts in the tropics on the synoptic to the subseasonal timescale but many models struggle to realistically represent this coupling. To study the underlying mechanisms of convectively coupled equatorial waves, we use aquaplanet simulations with the ICOsahedral Nonhydrostatic (ICON) model in a tropical channel configuration with a horizontal grid spacing of 13 km and with a prescribed zonally symmetric, latitudinally varying sea surface temperature. We compare simulations with parameterized and explicit deep/shallow convection. Using wave identification tools that are based on Fourier filtering in time and space and on projections of dynamical fields on theoretical wave patterns, we observe a predominance of equator-symmetric equatorial waves such as Kelvin waves and slow large-scale variability resembling the Madden-Julian Oscillation.

To diagnose interactions between the equatorial waves and convection, we use a moist static energy (MSE) framework. A budget analysis for column integrated MSE shows that spatial anomalies of the net shortwave and longwave radiation and the surface enthalpy flux increase the spatial variance of the column MSE, while advection dampens variability. For wave-convection coupling we employ a wave composite technique for the terms of the MSE budget. Results from this analysis will be presented at the conference. The same filtering tools and diagnostics are applied to a realistic ICON simulation with a 2.5 km horizontal grid spacing from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project.
Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling
Authors: Zhang Zhenyu , Laux Patrick , Arnault Joël , Wei Jianhui , Baade Jussi , Urban Marcel , Kunstmann Harald
Published: March 2021

Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.
Investigating the internal structure of the Antarctic Ice Sheet: the utility of isochrones for spatio-temporal ice sheet model calibration
Authors: Sutter Johannes , Fischer Hubertus , Eisen Olaf
Published: March 2021

Ice Sheet Models are a powerful tool to project the evolution of the Greenland and Antarctic Ice Sheets, and thus their future contribution to global sea-level changes. Probing the fitness of ice-sheet models to reproduce ongoing and past changes of the Greenland and Antarctic ice cover is a fundamental part of every modelling effort. However, benchmarking ice-sheet model data against real-world observations is a non-trivial process, as observational data comes with spatio-temporal gaps in coverage. Here, we present a new approach to assess the ability of ice-sheet models which makes use of the internal layering of the Antarctic Ice Sheet. We simulate observed isochrone elevations within the Antarctic Ice Sheet via passive Lagrangian tracers, highlighting that a good fit of the model to two dimensional datasets does not guarantee a good match against the three dimensional architecture of the ice-sheet and thus correct evolution over time. We show, that paleoclimate forcing schemes commonly used to drive ice-sheet models work well in the interior of the Antarctic Ice Sheet and especially along ice divides, but fail towards the ice-sheet margin. The comparison to isochronal horizons attempted here reveals, that simple heuristics of basal drag can lead to an overestimation of the vertical interior ice sheet flow especially over subglacial basins. Our model-observation intercomparison approach opens a new avenue to the improvement and tuning of current ice-sheet models via a more rigid constraint on model parameterisations and climate forcing which will benefit model-based estimates of future and past ice-sheet changes.
Joint inversion of receiver functions and apparent incidence angles to investigate the crustal structure of Mars
Authors: Joshi Rakshit , Knapmeyer-Endrun Brigitte , Mosegaard Klaus , Bissig Felix , Khan Amir , Panning Mark , Staehler Simon , Tauzin Benoit , Lekic Vedran , Scholz John-Robert , Davis Paul , Widmer-Schnidrig Rudolf , Garcia Raphael , Pinot Baptiste , Lognonné Philippe , Christensen Ulrich
Published: March 2021

Since InSight (the Interior Exploration using Geodesy and Heat Transport) landed 26 months ago and deployed an ultra sensitive broadband seismometer(SEIS) on the surface of Mars, around 500 seismic events of diverse variety have been detected, making it possible to directly analyze the subsurface properties of Mars for the very first time. One of the primary goals of the mission is to retrieve the crustal structure below the landing site. Current estimates differ by more than 100% for the average crustal thickness. Since data from orbital gravity measurementsprovide information on relative variations of crustal thickness but not absolute values, this landing site measurement could serve as a tie point to retrieve global crustal structure models. To do so, we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation which defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. Finally we use the Neighbourhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive the full uncertainty estimates for each model parameter. Before its application on data from InSight mission, we successfully tested the method on Mars synthetics and terrestrial data from various geological settings using both single and multiple events. Using the same method, we have previously been able to constrain the S-wave velocity and depth for the first inter-crustal layer of Mars between 1.7 to 2.1 km/s and 8 to 11 km, respectively. Here we present the results of applying this technique on our selected data set from the InSight mission. Results show that the data can be explained equally well by models with 2 or 3 crustal layers with constant velocities. Due to the limited data set it is difficult to resolve the ambiguity of this bi-modal solution. We therefore investigate information theoretic statistical tests as a model selection criteria and discuss their relevance and implications in seismological framework.
Development of a deep learning-based method for estimating surface soil moisture at high spatial resolution from Sentinel-1 satellite data
Authors: Simonsen Nicklas , Duan Zheng
Published: March 2021

Soil moisture content is an important hydrological and climatic variable with applications in a wide range of domains. The high spatial variability of soil moisture cannot be well captured from conventional point-based in-situ measurements. Remote sensing offers a feasible way to observe spatial pattern of soil moisture from regional to global scales. Microwave remote sensing has long been used to estimate Surface Soil Moisture Content (SSMC) at lower spatial resolutions (>1km), but few accurate options exist in the higher spatial resolution (<1km) domain. This study explores the capabilities of deep learning in the high-resolution domain of remotely sensed SSMC by using a Convolutional Neural Network (CNN) to estimate SSMC from Sentinel-1 acquired Synthetic Aperture Radar (SAR) imagery. The developed model incorporates additional SSMC predictors such as Normalized Difference Vegetation Index (NDVI), temperature, precipitation, and soil type to yield a more accurate estimation than traditional empirical formulas that focus solely on the conversion of backscatter signals to relative soil moisture. This also makes the developed model less sensitive to site-specific conditions and increases the model applicability outside the training domain. The model is developed and tested with in-situ soil moisture measurements in Denmark from a dense network maintained by HOBE (Danish Hydrological Observatory). The unique advantage of the developed model is its transferability across climate zones, which has been historically absent in many prior models. This would open up opportunities for high-resolution soil moisture mapping through remote sensing in areas with relatively few soil moisture gauges. A reliable high-resolution soil moisture platform at good temporal resolution would allow for more precise erosion modelling, flood forecasting, drought monitoring, and precision agriculture.
Interpreting Time-Varying Processes using Empirical Data
Authors: Hobé Alex , Tryggvason Ari , Almqvist Bjarne , Gudmundsson Olafur
Published: March 2021

Time-varying processes present both challenges and opportunities when interpreting tomographic models. The challenges mainly arise from differences between a method’s temporal and spatial resolution, and the size and timing of the physical processes. A mismatch here will produce a weighted average of the subsurface changes in models using time-dependent tomography. Even when there is such a mismatch, there are clear benefits from studying time-varying processes.

Many different variables are packed into geophysical properties. Seismic velocities, for example, change due to porosity, fluid presence, fluid phase, fractures, and fracture properties, among other factors. This makes interpretation non-unique. Tomographic changes due to time-varying processes help reduce the possibilities for interpretation, especially when integrating multiple geophysical methods. Because tomographic methods can also produce artificial changes between models (Hobé et al., 2021), an important question in time-dependent tomography becomes:
 
What is the theoretical magnitude of changes in geophysical properties in a time-varying area?

As an initial answer, we present an overview of empirical data from the IMAGE project, which investigated the Reykjanes Peninsula, Iceland. This overview shows the inherent temporal variability of this volcano-tectonic region. In the lab, geophysical properties changed as much as 30% due to, e.g., fracturing, fracture healing, fluid-phase changes, and changes in fluid saturation. All these phenomena are common occurrences in this area, which hosts several volcanic systems with hydrothermal and seismic activity. These phenomena also have a secondary impact on how the empirical data should be interpreted, which is usually underestimated or overlooked in tomographic interpretations: These time-varying processes can strongly affect effective pressures, which is one of the main variables in the empirical data. To show the magnitude of this oversight, we present examples where effective pressure is affected, along with the theoretical changes in geophysical properties. Lastly, we show how the inclusion of effective pressures in interpretation can aid in the identification of time-varying processes.

 

Hobé, A., Gudmundsson, O., Tryggvason, A., and the SIL seismological group (2021): Imaging the 2010-2011 inflationary source at Krýsuvík, SW Iceland, using time-dependent Vp/Vs tomography, in Proceedings World Geothermal Congress 2020, Forthcoming
Connecting solar flare hard X-ray spectra to in-situ electron spectra using RHESSI and STEREO/SEPT observations
Authors: Dresing Nina , Warmuth Alexander , Effenberger Frederic , Klein Ludwig , Glesener Lindsay , Musset Sophie , Bruedern Maximilian
Published: March 2021

In-situ observations of solar energetic particle events are determined by a combination of acceleration, injection, and transport processes which are often hard to disentangle. However, the energy spectrum of impulsive electron events is believed to carry the imprint of the flare acceleration process which can be studied by analyzing the hard X-ray (HXR) spectrum of the flare.

Using STEREO/SEPT electron data of the whole STEREO mission we have identified 64 solar energetic electron event candidates where the HXR solar counterpart of the event was observed by RHESSI. After cleaning of the data set and an independent verification by the timing of associated interplanetary type III radio bursts, we find 17 events which lend themselves for a comparison of the spectral indices observed in situ and at the Sun.

Special attention is paid to the choice of the in-situ electron spectral index used for comparison as most of the events show spectral transitions (breaks) in the measurement range of SEPT. We find that both the lower and higher spectral indices correlate similarly well with the HXR spectra yielding correlation coefficients of 0.8 but indicating opposite relations with the flare spectrum in terms of the thin- or thick target model. The correlations show no dependence on the electron onset delay, nor on the longitudinal separation between flare and spacecraft magnetic footpoint at the Sun. However, the correlations increase, if only events with significant anisotropy are used indicating that transport effects play a role in shaping the spectra observed in-situ. We will discuss the different transport effects that need to be taken into account and which may even lead to a vanishing imprint of the flare acceleration.
Thermal and multispectral images from Unmanned Aerial Vehicles (UAVs) for water presence detection in temporary streams: first results
Authors: Micieli Massimo , Botter Gianluca , Mendicino Giuseppe , Senatore Alfonso
Published: March 2021

UAVs (Unmanned Aerial Vehicles) are increasingly used for monitoring river networks with a broad range of purposes. In this contribution, we focus on the use of multispectral sensors, either in the thermal infrared band LWIR (Long-wavelength infrared, 8-15 µm) or in the infrared band NIR (Near-infrared, 0.75-1.4 µm) to map network dynamics in temporary streams. Specifically, we discuss the first results of a set of surveys carried out in 2020 within a small river catchment located in northern Calabria (southern Italy), as part of the research activities of the ERC-funded DyNET project. Preliminary, a rigorous methodology was identified to perform on-site surveys and to process and analyse the acquired images. Experimental results show that the combined use of LWIR and NIR sensors is a suitable solution for detecting water presence in channels characterized by different hydraulic and morphologic conditions. LWIR sensors alone allow one to discriminate water presence only when the thermal contrast with the surrounding environment is high. On the other hand, NIR sensors permit to detect the presence of water in most of the analyzed settings through the estimate of the Normalized Difference Water Index (NDWI). However, NIR sensors can be misled in case of shallow water depth, due to the NIR radiation emitted by the riverbed merging with that of the water. Overall, the study demonstrates that a combined LWIR/NIR approach allows addressing a broader range of conditions. Moreover, the information provided can be further enhanced by combining it with geomorphologic information and basic hydraulic concepts.
Application of deep learning methods for urban water demand forecast modelling
Authors: G Rajakumar Anjana , Anthony Avi , Kumar Vinoth
Published: March 2021

Water demand predictions forms an integral part of sustainable management practices for water supply systems. Demand prediction models aides in water system maintenance, expansions, daily operational planning and in the development of an efficient decision support system based on predictive analytics. In recent years, it has also found wide application in real-time control and operation of water systems as well. However, short term water demand forecasting is a challenging problem owing to the frequent variations present in the urban water demand patterns. There are numerous methods available in literature that deals with water demand forecasting. These methods can be roughly classified into statistical and machine learning methods. The application of deep learning methods for forecasting water demands is an upcoming research area that has found immense traction due to its ability to provide accurate and scalable models. But there are only a few works which compare and review these methods when applied to a water demand dataset. Hence, the main objective of this work is the application of different commonly used deep learning methods for development of a short-term water demand forecast model for a real-world dataset. The algorithms studied in this work are (i) Multi-Layer Perceptron (MLP) (ii) Gated Recurrent Unit (GRU) (iii) Long Short-Term Memory (LSTM) (iv) Convolutional Neural Networks (CNN) and (v) the hybrid algorithm CNN-LSTM. Optimal supervised learning framework required for forecasting the one day ahead water demand for the study area is also identified. The dataset used in this study is from Hillsborough County, Florida, US. The water demand data was available for a duration of 10 months and the data frequency is about once per hour. These algorithms were evaluated based on the (1) Mean Absolute Percentage Error (MAPE) and (ii) Root Mean Squared Error (RMSE) values. Visual comparison of the predicted and true demand plots was also employed to check the prediction accuracy. It was observed that, the RMSE and MAPE values were minimal for the supervised learning framework that used the previous 24-hour data as input. Also, with respect to the forecast accuracy, CNN-LSTM performed better than the other methods for demand forecast, followed by MLP. MAPE values for the developed deep learning models ranged from 5% to 25%. The quantity, frequency and quality of data was also found to have substantial impact on the accuracy of the forecast models developed. In the CNN-LSTM based forecast model, the CNN component was found to effectively extract the inherent characteristics of historical water consumption data such as the trend and seasonality, while the LSTM part was able to reflect on the long-term historical process and future trend. Thus, its water demand prediction accuracy was improved compared to the other methods such as GRU, MLP, CNN and LSTM.
A new simulation tool for automatic dilute and dense gas dispersion modelling 
Authors: Dioguardi Fabio , Massaro Silvia , Chiodini Giovanni , Costa Antonio , Folch Arnau , Macedonio Giovanni , Sandri Laura , Selva Jacopo
Published: March 2021

The emission of volcanic gases can occur both during volcanic eruptions and in quiescent stages of the volcanic activity. This process can affect the air quality in the areas downwind; in fact, many gas species can be a threat to human health and even life at concentrations and doses above species-specific thresholds. Gas emissions can be of different types, the two main categories being dilute passive degassing and heavy gas flow. The former occurs when the gas concentration is low and/or temperature is high, hence its density is lower than the atmospheric density; the latter takes place when the gas density is higher than the atmosphere and the gas accumulates onto the ground and may flow as a gravity current more or less affected by the wind. Examples of the first and second types of emissions are fumaroles and limnic explosions, respectively.

Numerical modelling is one of the approaches used to quantify the hazard related to these processes. Ideally, for hazard quantification purposes numerous simulations originating from varying the most important input parameters (e.g. wind field, emission rates, etc.) in their range of uncertainty should be carried out. The whole process of gas dispersion modelling is time consuming, since it starts with the assessment of the wind field with an ad-hoc meteorological model, proceeds with the actual gas dispersion simulation and concludes with the post-processing stage. In order to simplify the whole workflow with the final aim to manage numerous simultaneous simulations for hazard assessment applications, we created APVGDM (Automatic Probabilistic Volcanic Gas Dispersion Modelling), a simulation tool made of a collection of Python scripts. APVGDM is interfaced with two dispersion models that can be selected by the user depending on the application of interest: a dilute (DISGAS) and a dense gas (TWODEE) dispersion model. The post-processing script is capable of building Empirical Cumulative Distribution Functions (ECDF) of the gas concentrations combining the outputs of multiple simulations; the ECDF can be interrogated by the user to produce outputs at the desired exceedance probability. Here we present APVGDM and some application examples showing the wide range of options that the tool offers.
High pressure, halogen-bearing melt in ultra-high temperature felsic granulites of the Central Maine Terrane, Connecticut (US)
Authors: Ferrero Silvio , Ague Jay J. , O'Brien Patrick J. , Wunder Bernd , Remusat Laurent , Ziemann Martin A. , Axler Jennifer
Published: March 2021

Inclusions of relic high pressure melts provide information on the fate of crustal rocks in the deep roots of orogens during collision and crustal thickening, including at extreme temperature conditions exceeding 1000°C. However, discoveries of high pressure melt inclusions are still a relative rarity among case studies of inclusions in metamorphic minerals. Here we present the results of experimental and microchemical investigations of nanogranitoids in garnets from the felsic granulites of the Central Maine Terrane (Connecticut, US). Their successful experimental re-homogenization at ~2 GPa confirms that they originally were trapped portions of deep melts and makes them the first direct evidence of high pressure during peak metamorphism and melting for these felsic granulites. The trapped melt has a hydrous, granitic, and peraluminous character typical of crustal melts from metapelites. This melt is higher in mafic components (FeO and MgO) than most of the nanogranitoids investigated previously, likely the result of the extreme melting temperatures – well above 1000°C. This is the first natural evidence of the positive correlation between temperature and mafic character of the melt, a trend previously supported only by experimental evidence. Moreover, it poses a severe caveat against the common assumption that partial melts from metasediments at depth are always leucogranitic in composition. NanoSIMS measurement on re-homogenized inclusions show significant amounts of CO2, Cl and F. Halogen abundance in the melt is considered to be a proxy for the presence of brines (strongly saline fluids) at depth. Brines are known to shift the melting temperatures of the system toward higher values, and may have been responsible for delaying melt production via biotite dehydration melting until these rocks reached extreme temperatures of more than 1000°C, rather than 800-850°C as commonly observed for these reactions.
Wave-induced constituent transport in the middle and upper atmosphere
Authors: Guarino Maria Vittoria , Feng Wuhu , Gardner Chester , Marsh Daniel , Plane John
Published: March 2021

Atmospheric gravity waves generated in the troposphere by a number of sources (convection, frontogenesis, orography etc.) can travel great vertical distances, propagating upwards to 80 - 120km where they influence the chemical and dynamical structure of the Mesosphere and Lower Thermosphere (MLT).

Current chemistry-climate models represent gravity waves, and their impact on the temperature and the chemical composition of the atmosphere, by means of parameterizations that take into account the turbulence and the mixing caused by breaking waves but largely neglect the dynamical and chemical constituent transport by vertically propagating non-breaking waves.

We present initial results from the WAVECHASM (Wave-Induced Transport of Chemically Active Species in the Mesosphere and Lower Thermosphere) project. By making use of a recent novel theoretical approach, where the effective wave diffusivity is expressed as a function of the eddy diffusivity and of the variances of the temperature perturbation and lapse rate fluctuations, the WAVECHASM project aims to incorporate the missing transport processes into global atmospheric chemistry models. We will show here that it is possible to modify the current gravity wave drag parameterization of NCAR’s Whole Atmosphere Community Climate Model (WACCM) to explicitly account for the wave-driven vertical mixing associated with non-breaking gravity waves. This additional source of vertical mixing is expected to induce significant constituent transport in the upper atmosphere.