Project acronym CoreSat
Project Dynamics of Earth’s core from multi-satellite observations
Researcher (PI) Christopher FINLAY
Host Institution (HI) DANMARKS TEKNISKE UNIVERSITET
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary Earth's magnetic field plays a fundamental role in our planetary habitat, controlling interactions between the Earth and the solar wind. Here, I propose to use magnetic observations, made simultaneously by multiple satellites, along with numerical models of outer core dynamics, to test whether convective processes can account for ongoing changes in the field. The geomagnetic field is generated by a dynamo process within the core converting kinetic energy of the moving liquid metal into magnetic energy. Yet observations show a region of persistently weak field in the South Atlantic that has grown in size in recent decades. Pinning down the core dynamics responsible for this behaviour is essential if we are to understand the detailed time-dependence of the geodynamo, and to forecast future field changes.
Global magnetic observations from the Swarm constellation mission, with three identical satellites now carrying out the most detailed ever survey of the geomagnetic field, provide an exciting opportunity to probe the dynamics of the core in exquisite detail. To exploit this wealth of data, it is urgent that contaminating magnetic sources in the lithosphere and ionosphere are better separated from the core-generated field. I propose to achieve this, and to test the hypothesis that core convection has controlled the recent field evolution in the South Atlantic, via three interlinked projects. First I will co-estimate separate models for the lithospheric and core fields, making use of prior information from crustal geology and dynamo theory. In parallel, I will develop a new scheme for isolating and removing the signature of polar ionospheric currents, better utilising ground-based data. Taking advantage of these improvements, data from Swarm and previous missions will be reprocessed and then assimilated into a purpose-built model of quasi-geostrophic core convection.
Summary
Earth's magnetic field plays a fundamental role in our planetary habitat, controlling interactions between the Earth and the solar wind. Here, I propose to use magnetic observations, made simultaneously by multiple satellites, along with numerical models of outer core dynamics, to test whether convective processes can account for ongoing changes in the field. The geomagnetic field is generated by a dynamo process within the core converting kinetic energy of the moving liquid metal into magnetic energy. Yet observations show a region of persistently weak field in the South Atlantic that has grown in size in recent decades. Pinning down the core dynamics responsible for this behaviour is essential if we are to understand the detailed time-dependence of the geodynamo, and to forecast future field changes.
Global magnetic observations from the Swarm constellation mission, with three identical satellites now carrying out the most detailed ever survey of the geomagnetic field, provide an exciting opportunity to probe the dynamics of the core in exquisite detail. To exploit this wealth of data, it is urgent that contaminating magnetic sources in the lithosphere and ionosphere are better separated from the core-generated field. I propose to achieve this, and to test the hypothesis that core convection has controlled the recent field evolution in the South Atlantic, via three interlinked projects. First I will co-estimate separate models for the lithospheric and core fields, making use of prior information from crustal geology and dynamo theory. In parallel, I will develop a new scheme for isolating and removing the signature of polar ionospheric currents, better utilising ground-based data. Taking advantage of these improvements, data from Swarm and previous missions will be reprocessed and then assimilated into a purpose-built model of quasi-geostrophic core convection.
Max ERC Funding
1 828 708 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
Project acronym FOCUS
Project Fiber Optic Cable Use for Seafloor studies of earthquake hazard and deformation
Researcher (PI) Marc-André GUTSCHER
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), PE10, ERC-2017-ADG
Summary Two-thirds of the Earth’s surface is covered by water and thus largely inaccessible to modern networks of seismological instruments. The FOCUS project is poised to revolutionize seismic monitoring of the seafloor through a novel use of fiber optic cables to improve hazard assessment and increase early warning capability. Laser reflectometry using BOTDR, commonly used for structural health monitoring of large-scale engineering structures (e.g. - bridges, dams, pipelines, etc.), can measure very small strains (< 1 mm) at very large distances (10 - 200 km). It has never been used to monitor deformation caused by active faults on the seafloor. The objective of the FOCUS project is to demonstrate that this technique can measure small (1 - 2 cm) displacements on a primary test site offshore Sicily where the 28 km long EMSO Catania cable crosses the recently mapped North Alfeo Fault. BOTDR observations must be calibrated by other independent measurements. Therefore, targeted marine geophysical surveys of the seafloor along the trace of the cable and faults are planned, with micro-bathymetry, high-resolution seismics, seafloor seismic stations and use of seafloor geodetic instruments to quantify fault displacement. Once the BOTDR fault-monitoring technique has been tested and calibrated offshore Sicily, the goal is to expand it to other fiber optic cable networks, either existing research networks in earthquake hazard zones (Japan, Cascadia) or to the Mediterranean region through access to retired telecommunication cables, or through the development of dual-use cables with industry partners, (two of the anticipated outcomes of the FOCUS project). The novel secondary use of fiber optic cables as described by FOCUS represents a potentially tremendous breakthrough in seismology, tectonics and natural hazard early warning capability, one that could turn Earth’s future undersea communication infrastructure into a seismological monitoring network of unprecedented scale.
Summary
Two-thirds of the Earth’s surface is covered by water and thus largely inaccessible to modern networks of seismological instruments. The FOCUS project is poised to revolutionize seismic monitoring of the seafloor through a novel use of fiber optic cables to improve hazard assessment and increase early warning capability. Laser reflectometry using BOTDR, commonly used for structural health monitoring of large-scale engineering structures (e.g. - bridges, dams, pipelines, etc.), can measure very small strains (< 1 mm) at very large distances (10 - 200 km). It has never been used to monitor deformation caused by active faults on the seafloor. The objective of the FOCUS project is to demonstrate that this technique can measure small (1 - 2 cm) displacements on a primary test site offshore Sicily where the 28 km long EMSO Catania cable crosses the recently mapped North Alfeo Fault. BOTDR observations must be calibrated by other independent measurements. Therefore, targeted marine geophysical surveys of the seafloor along the trace of the cable and faults are planned, with micro-bathymetry, high-resolution seismics, seafloor seismic stations and use of seafloor geodetic instruments to quantify fault displacement. Once the BOTDR fault-monitoring technique has been tested and calibrated offshore Sicily, the goal is to expand it to other fiber optic cable networks, either existing research networks in earthquake hazard zones (Japan, Cascadia) or to the Mediterranean region through access to retired telecommunication cables, or through the development of dual-use cables with industry partners, (two of the anticipated outcomes of the FOCUS project). The novel secondary use of fiber optic cables as described by FOCUS represents a potentially tremendous breakthrough in seismology, tectonics and natural hazard early warning capability, one that could turn Earth’s future undersea communication infrastructure into a seismological monitoring network of unprecedented scale.
Max ERC Funding
3 487 911 €
Duration
Start date: 2018-10-01, End date: 2023-09-30
Project acronym GEO-4D
Project Geodetic data assimilation: Forecasting Deformation with InSAR
Researcher (PI) Romain JOLIVET
Host Institution (HI) ECOLE NORMALE SUPERIEURE
Call Details Starting Grant (StG), PE10, ERC-2017-STG
Summary Recent space-based geodetic measurements of ground deformation suggest a paradigm shift is required in our understanding of the behaviour of active tectonic faults. The classic view of faults classified in two groups – the locked faults prone to generate earthquakes and the creeping faults releasing stress through continuous aseismic slip – is now obscured by more and more studies shedding light on a wide variety of seismic and aseismic slip events of variable duration and size. What physical mechanism controls whether a tectonic fault will generate a dynamic, catastrophic rupture or gently release energy aseismically? Answering such a fundamental question requires a tool for systematic and global detection of all modes of slip along active faults.
The launch of the Sentinel 1 constellation is a game changer as it provides, from now on, systematic Radar mapping of all actively deforming regions in the world with a 6-day return period. Such wealth of data represents an opportunity as well as a challenge we need to meet today. In order to expand the detection and characterization of all slip events to a global scale, I will develop a tool based on machine learning procedures merging the detection capabilities of all data types, including Sentinel 1 data, to build time series of ground motion.
The first step is the development of a geodetic data assimilation method with forecasting ability toward the first re-analysis of active fault motion and tectonic phenomena. The second step is a validation of the method on three faults, including the well-instrumented San Andreas (USA) and Longitudinal Valley faults (Taiwan) and the North Anatolian Fault (NAF, Turkey). I will deploy a specifically designed GPS network along the NAF to compare with outputs of our method. The third step is the intensive use of the algorithm on a global scale to detect slip events of all temporal and spatial scales for a better understanding of the slip behaviour along all active continental faults.
Summary
Recent space-based geodetic measurements of ground deformation suggest a paradigm shift is required in our understanding of the behaviour of active tectonic faults. The classic view of faults classified in two groups – the locked faults prone to generate earthquakes and the creeping faults releasing stress through continuous aseismic slip – is now obscured by more and more studies shedding light on a wide variety of seismic and aseismic slip events of variable duration and size. What physical mechanism controls whether a tectonic fault will generate a dynamic, catastrophic rupture or gently release energy aseismically? Answering such a fundamental question requires a tool for systematic and global detection of all modes of slip along active faults.
The launch of the Sentinel 1 constellation is a game changer as it provides, from now on, systematic Radar mapping of all actively deforming regions in the world with a 6-day return period. Such wealth of data represents an opportunity as well as a challenge we need to meet today. In order to expand the detection and characterization of all slip events to a global scale, I will develop a tool based on machine learning procedures merging the detection capabilities of all data types, including Sentinel 1 data, to build time series of ground motion.
The first step is the development of a geodetic data assimilation method with forecasting ability toward the first re-analysis of active fault motion and tectonic phenomena. The second step is a validation of the method on three faults, including the well-instrumented San Andreas (USA) and Longitudinal Valley faults (Taiwan) and the North Anatolian Fault (NAF, Turkey). I will deploy a specifically designed GPS network along the NAF to compare with outputs of our method. The third step is the intensive use of the algorithm on a global scale to detect slip events of all temporal and spatial scales for a better understanding of the slip behaviour along all active continental faults.
Max ERC Funding
1 499 125 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym INTERACTION
Project Cloud-cloud interaction in convective precipitation
Researcher (PI) Jan Olaf Mirko Härter
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary State-of-the-art simulations and observations highlight the self-organization of convective clouds. Our recent work shows two aspects: these clouds are capable of unexpected increase in extreme precipitation when temperature rises; interactions between clouds produce the extremes. As clouds interact, they organize in space and carry a memory of past interaction and precipitation events. This evidence reveals a severe shortcoming of the conventional separation into "forcing" and "feedback" in climate model parameterizations, namely that the "feedback" develops a dynamics of its own, thus driving the extremes. The major scientific challenge tackled in INTERACTION is to make a ground-breaking departure from the established paradigm of "quasi-equilibrium" and instantaneous convective adjustment, traditionally used for parameterization of "sub-grid-scale processes" in general circulation models. To capture convective self-organization and extremes, the out-of-equilibrium cloud field must be described. In INTERACTION, I will produce a conceptual model for the out-of-equilibrium system of interacting clouds. Once triggered, clouds precipitate on a short timescale, but then relax in a "recovery" state where further precipitation is suppressed. Interaction with the surroundings occurs through cold pool outflow,facilitating the onset of new events in the wake. I will perform tailored numerical experiments using cutting-edge large-eddy simulations and very-high-resolution observational analysis to determine the effective interactions in the cloud system. Going beyond traditional forcing-and-feedback descriptions, I emphasize gradual self-organization with explicit temperature dependence. The list of key variables of atmospheric water vapor, temperature and precipitation must therefore be amended by variables describing organization. Capturing the self-organization of convection is essential for understanding of the risk of precipitation extremes today and in a future climate.
Summary
State-of-the-art simulations and observations highlight the self-organization of convective clouds. Our recent work shows two aspects: these clouds are capable of unexpected increase in extreme precipitation when temperature rises; interactions between clouds produce the extremes. As clouds interact, they organize in space and carry a memory of past interaction and precipitation events. This evidence reveals a severe shortcoming of the conventional separation into "forcing" and "feedback" in climate model parameterizations, namely that the "feedback" develops a dynamics of its own, thus driving the extremes. The major scientific challenge tackled in INTERACTION is to make a ground-breaking departure from the established paradigm of "quasi-equilibrium" and instantaneous convective adjustment, traditionally used for parameterization of "sub-grid-scale processes" in general circulation models. To capture convective self-organization and extremes, the out-of-equilibrium cloud field must be described. In INTERACTION, I will produce a conceptual model for the out-of-equilibrium system of interacting clouds. Once triggered, clouds precipitate on a short timescale, but then relax in a "recovery" state where further precipitation is suppressed. Interaction with the surroundings occurs through cold pool outflow,facilitating the onset of new events in the wake. I will perform tailored numerical experiments using cutting-edge large-eddy simulations and very-high-resolution observational analysis to determine the effective interactions in the cloud system. Going beyond traditional forcing-and-feedback descriptions, I emphasize gradual self-organization with explicit temperature dependence. The list of key variables of atmospheric water vapor, temperature and precipitation must therefore be amended by variables describing organization. Capturing the self-organization of convection is essential for understanding of the risk of precipitation extremes today and in a future climate.
Max ERC Funding
1 314 800 €
Duration
Start date: 2018-07-01, End date: 2023-06-30
Project acronym Sea2Cloud
Project Are marine living microorganisms influencing clouds?
Researcher (PI) Karine SELLEGRI
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary Earth, as a whole, can be considered as a living organism emitting gases and particles in its atmosphere, in order to regulate its own temperature (Lovelock, 1988). In particular oceans, which cover 70% of the Earth, may respond to climate change by emitting different species under different environmental conditions. At the global scale, a large fraction of the aerosol number concentration is formed by nucleation of low-volatility gas-phase compounds, a process that is expected to ultimately determine the concentrations of Cloud Condensation Nuclei (CCN). Nucleation occurrence over open oceans is still debated, due to scarce observational data sets and instrumental limitations, although our recent findings suggest biologically driven nucleation from seawater emissions. Marine aerosol can also be emitted to the atmosphere as primary particles via bubble bursting, among which living microorganisms are suspected to act as excellent ice nuclei (IN) and impact clouds precipitation capacities. The main goal of this proposal is to investigate how marine emissions from living microorganisms can influence CCN, IN and ultimately cloud properties. We will investigate the whole process chain of gas-phase emissions, nucleation and growth through the atmospheric column, and impact on the CCN population. We will also quantify marine primary bioaerosol emissions and evaluate how they impact IN and cloud precipitation capabilities. Experiments will be performed in the Southern Hemisphere, especially sensitive to the natural aerosol concentration variability. We will use an original approach of field mesocosms enclosing the air-sea interface, to link marine emissions to the biogeochemical properties of natural seawater, combined with ambient aerosol measurements simultaneously at low and high altitude sites. At last, a modelling study will help merging process studies and ambient measurements, and assess the role of biologically driven marine emissions on cloud properties.
Summary
Earth, as a whole, can be considered as a living organism emitting gases and particles in its atmosphere, in order to regulate its own temperature (Lovelock, 1988). In particular oceans, which cover 70% of the Earth, may respond to climate change by emitting different species under different environmental conditions. At the global scale, a large fraction of the aerosol number concentration is formed by nucleation of low-volatility gas-phase compounds, a process that is expected to ultimately determine the concentrations of Cloud Condensation Nuclei (CCN). Nucleation occurrence over open oceans is still debated, due to scarce observational data sets and instrumental limitations, although our recent findings suggest biologically driven nucleation from seawater emissions. Marine aerosol can also be emitted to the atmosphere as primary particles via bubble bursting, among which living microorganisms are suspected to act as excellent ice nuclei (IN) and impact clouds precipitation capacities. The main goal of this proposal is to investigate how marine emissions from living microorganisms can influence CCN, IN and ultimately cloud properties. We will investigate the whole process chain of gas-phase emissions, nucleation and growth through the atmospheric column, and impact on the CCN population. We will also quantify marine primary bioaerosol emissions and evaluate how they impact IN and cloud precipitation capabilities. Experiments will be performed in the Southern Hemisphere, especially sensitive to the natural aerosol concentration variability. We will use an original approach of field mesocosms enclosing the air-sea interface, to link marine emissions to the biogeochemical properties of natural seawater, combined with ambient aerosol measurements simultaneously at low and high altitude sites. At last, a modelling study will help merging process studies and ambient measurements, and assess the role of biologically driven marine emissions on cloud properties.
Max ERC Funding
1 999 329 €
Duration
Start date: 2018-07-01, End date: 2023-06-30
Project acronym SEISMAZE
Project Data-intensive analysis of seismic tremors and long period events: a new paradigm for understanding transient deformation processes in active geological systems
Researcher (PI) NIKOLAI CHAPIRO
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), PE10, ERC-2017-ADG
Summary Seismic tremors form a broad class of signals generated by internal sources that are different from regular earthquakes. Volcanic tremors have been known for a long time, and tectonic tremors associated with seismogenic fault zones have been described more recently. While the physical origin of seismic tremors remains to be fully understood, they are related to slow transient energy release processes that occur in active geological systems during the accumulation of mechanical energy that is then released during catastrophic events, such as strong earthquakes or volcanic eruptions. Therefore, seismic tremors represent a unique source of information that can be used to understand the physics of these ‘preparation’ processes and to design new monitoring and forecasting approaches.
Modern digital seismological networks record huge numbers of tremors in different active regions, and breakthroughs can be achieved with systematic exploration of these observations that includes data analysis and physical modeling. My goal is to undertake such an effort via the development of a new unified framework for the study of seismic tremors. I plan to combine advanced methods for data mining, signal processing, and numerical simulations of the generating processes, to apply these to different large datasets of volcanic and tectonic tremors.
I will develop an innovative and holistic approach based on massive analysis of observations that requires high performance computing and will be combined with advanced physical modeling of the generating dynamical processes. This will produce the new framework that can be used on the one hand for an understanding of the physical tremor-generating mechanisms, and on other hand for the development of new adaptive methods for monitoring volcanoes and seismic faults. The implementation of these will involve machine learning approaches to gain information from continuous fluxes of data from dense seismological networks.
Summary
Seismic tremors form a broad class of signals generated by internal sources that are different from regular earthquakes. Volcanic tremors have been known for a long time, and tectonic tremors associated with seismogenic fault zones have been described more recently. While the physical origin of seismic tremors remains to be fully understood, they are related to slow transient energy release processes that occur in active geological systems during the accumulation of mechanical energy that is then released during catastrophic events, such as strong earthquakes or volcanic eruptions. Therefore, seismic tremors represent a unique source of information that can be used to understand the physics of these ‘preparation’ processes and to design new monitoring and forecasting approaches.
Modern digital seismological networks record huge numbers of tremors in different active regions, and breakthroughs can be achieved with systematic exploration of these observations that includes data analysis and physical modeling. My goal is to undertake such an effort via the development of a new unified framework for the study of seismic tremors. I plan to combine advanced methods for data mining, signal processing, and numerical simulations of the generating processes, to apply these to different large datasets of volcanic and tectonic tremors.
I will develop an innovative and holistic approach based on massive analysis of observations that requires high performance computing and will be combined with advanced physical modeling of the generating dynamical processes. This will produce the new framework that can be used on the one hand for an understanding of the physical tremor-generating mechanisms, and on other hand for the development of new adaptive methods for monitoring volcanoes and seismic faults. The implementation of these will involve machine learning approaches to gain information from continuous fluxes of data from dense seismological networks.
Max ERC Funding
2 490 000 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym STROMATA
Project Micro-pyrites associated with organic material in ancient stromatolites: a new proxy attesting for their biogenicity
Researcher (PI) Johanna MARIN-CARBONNE
Host Institution (HI) UNIVERSITE JEAN MONNET SAINT-ETIENNE
Call Details Starting Grant (StG), PE10, ERC-2017-STG
Summary Identifying Archean fossil remains from the Earth’s early biosphere is ambitious and determining the biological origin and the associated metabolic pathways present in these fossils is one outstanding question in the bigger quest of how life evolved on Earth. Stromatolites and Microbially Induced Sedimentary Structures (MISS) are considered as one of the earliest evidence of Life in Earth’s history, and can be found from the Archean to the present time. Stromatolites are “attached laminated, sedimentary growth structure accretionary away from a point of initiation”, and their morphological comparison with actual structure prevail for assessing the microbial origin of ancient stromatolite in the geological record. However, experimental studies have shown that abiotic precipitation can also form structures with a similar morphology. Therefore stable isotope proxies have been used to identify past microbial metabolisms even if abiotic processes can also produce similar isotope composition. Therefore new biogenicity criteria are needed to be determined by studying modern and ancient stromatolites and by comparing them to abiotic experiment. Stromatolites and MISS contain submicrometer sulfides (pyrite) that can have recorded large isotopic variations, interpreted as reflecting the influence of various microbial metabolisms like microbial sulfate reduction and iron respiration. STROMATA proposes to define new criteria based on actual stromatolite and to test the earliest traces of life by studying in situ these nano-pyrites in various emblematic and well-characterized samples from the Archean. STROMATA will be the first far-reaching scientific in situ study of nano-pyrite in ancient (3.4 to 1.9 Ga) and modern microbial mats and stromatolites and will compare the results with experimentally produced abiotic pyrite. Due to the small scale of the pyrite, STROMATA will develop an original in situ approach by combining state of art techniques, SIMS, NanoSIMS, FEG-TEM, XANES.
Summary
Identifying Archean fossil remains from the Earth’s early biosphere is ambitious and determining the biological origin and the associated metabolic pathways present in these fossils is one outstanding question in the bigger quest of how life evolved on Earth. Stromatolites and Microbially Induced Sedimentary Structures (MISS) are considered as one of the earliest evidence of Life in Earth’s history, and can be found from the Archean to the present time. Stromatolites are “attached laminated, sedimentary growth structure accretionary away from a point of initiation”, and their morphological comparison with actual structure prevail for assessing the microbial origin of ancient stromatolite in the geological record. However, experimental studies have shown that abiotic precipitation can also form structures with a similar morphology. Therefore stable isotope proxies have been used to identify past microbial metabolisms even if abiotic processes can also produce similar isotope composition. Therefore new biogenicity criteria are needed to be determined by studying modern and ancient stromatolites and by comparing them to abiotic experiment. Stromatolites and MISS contain submicrometer sulfides (pyrite) that can have recorded large isotopic variations, interpreted as reflecting the influence of various microbial metabolisms like microbial sulfate reduction and iron respiration. STROMATA proposes to define new criteria based on actual stromatolite and to test the earliest traces of life by studying in situ these nano-pyrites in various emblematic and well-characterized samples from the Archean. STROMATA will be the first far-reaching scientific in situ study of nano-pyrite in ancient (3.4 to 1.9 Ga) and modern microbial mats and stromatolites and will compare the results with experimentally produced abiotic pyrite. Due to the small scale of the pyrite, STROMATA will develop an original in situ approach by combining state of art techniques, SIMS, NanoSIMS, FEG-TEM, XANES.
Max ERC Funding
1 060 250 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym TimeMan
Project RHEOLOGY OF EARTH MATERIALS: CLOSING THE GAP BETWEEN TIMESCALES IN THE LABORATORY AND IN THE MANTLE
Researcher (PI) Patrick CORDIER
Host Institution (HI) UNIVERSITE DE LILLE
Call Details Advanced Grant (AdG), PE10, ERC-2017-ADG
Summary Most large-scale geological process such as plate tectonics or mantle convection involve plastic deformation of rocks. With most recent developments, constraining their rheological properties at natural strain-rates is something we can really achieve in the decade to come.
Presently, these theological properties are described with empirical equations which are fitted on macroscopic, average properties, obtained in laboratory experiments performed at human timescales. Their extrapolation to Earth’s conditions over several orders of magnitude is highly questionable as demonstrated by recent comparison with surface geophysical observables.
Strain rates couple space and time. We cannot expand time, but we can now reduce length scales. By using the new generation of nanomechanical testing machines in transmission electron microscopes, we can have access to elementary deformation mechanisms and, more importantly, we can measure the key physical parameters which control their dynamics. At this scale, we can have access to very slow mechanisms which were previously out of reach. This approach can be complemented by numerical modelling. By using the recent developments in modelling the so-called “rare events”, we will be able to model mechanisms in the same timescales as nanomechanical testing.
By combining, nanomechanical testing and advanced numerical modelling of elementary processes I propose to elaborate a new generation of rheological laws, based on the physics of deformation, which will explicitly involve time (i.e. strain rate) and will require no extrapolation to be applied to natural processes.
Applied to olivine, the main constituent of the upper mantle, this will provide the first robust, physics-based rheological laws for the lithospheric and asthenospheric mantle to be compared with surface observables and incorporated in geophysical convection models.
Summary
Most large-scale geological process such as plate tectonics or mantle convection involve plastic deformation of rocks. With most recent developments, constraining their rheological properties at natural strain-rates is something we can really achieve in the decade to come.
Presently, these theological properties are described with empirical equations which are fitted on macroscopic, average properties, obtained in laboratory experiments performed at human timescales. Their extrapolation to Earth’s conditions over several orders of magnitude is highly questionable as demonstrated by recent comparison with surface geophysical observables.
Strain rates couple space and time. We cannot expand time, but we can now reduce length scales. By using the new generation of nanomechanical testing machines in transmission electron microscopes, we can have access to elementary deformation mechanisms and, more importantly, we can measure the key physical parameters which control their dynamics. At this scale, we can have access to very slow mechanisms which were previously out of reach. This approach can be complemented by numerical modelling. By using the recent developments in modelling the so-called “rare events”, we will be able to model mechanisms in the same timescales as nanomechanical testing.
By combining, nanomechanical testing and advanced numerical modelling of elementary processes I propose to elaborate a new generation of rheological laws, based on the physics of deformation, which will explicitly involve time (i.e. strain rate) and will require no extrapolation to be applied to natural processes.
Applied to olivine, the main constituent of the upper mantle, this will provide the first robust, physics-based rheological laws for the lithospheric and asthenospheric mantle to be compared with surface observables and incorporated in geophysical convection models.
Max ERC Funding
2 499 400 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym TUVOLU
Project Tundra biogenic volatile emissions in the 21st century
Researcher (PI) Riikka Tiivi Mariisa Rinnan
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary Biogenic volatile organic compounds (BVOCs) influence atmospheric oxidation causing climate feedback thought to be especially significant in remote areas with low anthropogenic emissions, such as the Arctic. Still, we do not understand the dynamics and impact of climatic and biotic BVOC emission drivers in arctic and alpine tundra, which are highly temperature-sensitive BVOC sources.
TUVOLU will redefine tundra BVOC emission estimates to account for rapid and dramatic climate warming accompanied by effects of vegetation change, permafrost thaw, insect outbreaks and herbivory using multidisciplinary, established and novel methodology.
We will quantify the relationships between leaf and canopy temperatures and BVOC emissions to improve BVOC emission model predictions of emission rates in low-statured tundra vegetation, which efficiently heats up. We will experimentally determine the contribution of induced BVOC emissions from insect herbivory in the warming Arctic by field manipulation experiments addressing basal herbivory and insect outbreaks and by stable isotope labelling to identify sources of the induced emission. Complementary laboratory assessment will determine if permafrost thaw leads to significant BVOC emissions from thawing processes and newly available soil processes, or if released BVOCs are largely taken up by soil microbes. We will also use a global network of existing climate warming experiments in alpine tundra to assess how the BVOC emissions from tundra vegetation world-wide respond to climate change.
Measurement data will help develop and parameterize BVOC emission models to produce holistic enhanced predictions for global tundra emissions. Finally, modelling will be used to estimate emission impact on tropospheric ozone concentrations and secondary organic aerosol levels, producing the first assessment of arctic BVOC-mediated feedback on regional air quality and climate.
Summary
Biogenic volatile organic compounds (BVOCs) influence atmospheric oxidation causing climate feedback thought to be especially significant in remote areas with low anthropogenic emissions, such as the Arctic. Still, we do not understand the dynamics and impact of climatic and biotic BVOC emission drivers in arctic and alpine tundra, which are highly temperature-sensitive BVOC sources.
TUVOLU will redefine tundra BVOC emission estimates to account for rapid and dramatic climate warming accompanied by effects of vegetation change, permafrost thaw, insect outbreaks and herbivory using multidisciplinary, established and novel methodology.
We will quantify the relationships between leaf and canopy temperatures and BVOC emissions to improve BVOC emission model predictions of emission rates in low-statured tundra vegetation, which efficiently heats up. We will experimentally determine the contribution of induced BVOC emissions from insect herbivory in the warming Arctic by field manipulation experiments addressing basal herbivory and insect outbreaks and by stable isotope labelling to identify sources of the induced emission. Complementary laboratory assessment will determine if permafrost thaw leads to significant BVOC emissions from thawing processes and newly available soil processes, or if released BVOCs are largely taken up by soil microbes. We will also use a global network of existing climate warming experiments in alpine tundra to assess how the BVOC emissions from tundra vegetation world-wide respond to climate change.
Measurement data will help develop and parameterize BVOC emission models to produce holistic enhanced predictions for global tundra emissions. Finally, modelling will be used to estimate emission impact on tropospheric ozone concentrations and secondary organic aerosol levels, producing the first assessment of arctic BVOC-mediated feedback on regional air quality and climate.
Max ERC Funding
2 347 668 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
