Vedran Lekic
2017-07-06 01:33:30
Dear Colleagues,
We are organizing a special session at the 2017 AGU Fall meeting focusing
on Uncertainty Quantification titled "Frontiers of uncertainty
quantification in geoscientific inversion”. The session aims to provide a
cross-disciplinary view of research in the field and be inclusive to a wide
variety of work and applications (the abstract is copied below). We are
excited to have very broad support from the AGU sections of Seismology,
Study of Earth's Deep Interior, Geomagnetism, Paleomagnetism and
Electromagnetism, Hydrology, and Near Surface Geophysics:
https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session24490
We hope that this session will be of interest to you and that you and/or
your students will consider contributing an abstract.
The abstract deadline is 2 August 2017. The meeting will be held in New
Orleans, LA, from December 11-15, 2017.
Our apologies for any cross postings of this advertisement.
Best wishes,
Jan Dettmer
on behalf of the organizers:
Jan Dettmer (U Calgary)
Burke Minsley (USGS)
Anandaroop Ray (Chevron)
Vedran Lekic (U Maryland)
Thomas Bodin (U Lyon)
Kerry Key (UCSD)
Niklas Linde (U Lausanne)
Louise Pellerin (Green Geophysics)
*********************************************
Frontiers of uncertainty quantification in geoscientific inversion
Geoscientists employ inversion methods to infer Earth properties and
processes. These inferences are based on earth observations and described
by model parameters. However, incomplete and noisy observations, subjective
processing and inversion choices, non-uniqueness, and approximate physical
theory lead to parameter uncertainty. Therefore, robust interpretation of
inversion results requires uncertainty estimation, which relates parameter
knowledge to data errors. Rigorous methods for uncertainty quantification
are of great practical value across disciplines, particularly those
involving predictions, such as probabilistic hazard assessment or
hydrologic modeling. For instance, how uncertain are inferred locations of
unexploded ordnances, economic resources, or chemical contaminants? How
uncertain are tsunami predictions given uncertain earthquake rupture and
earth structure knowledge? To produce quantitative answers, inversion
methods must account for observational errors, model limitations and reduce
subjective choices. We invite submissions on all aspects of uncertainty
quantification, including theoretical advances and practical applications
across all fields of geosciences.
*********************************************
--
*Vedran Leki**ć*
Asst. Prof. Geology
Asst. Prof. Applied Mathematics & Statistics and Scientific Computation
University of Maryland, College Park
P: 301-405-4086, F: 301-314-9661
geol.umd.edu/~ved
We are organizing a special session at the 2017 AGU Fall meeting focusing
on Uncertainty Quantification titled "Frontiers of uncertainty
quantification in geoscientific inversion”. The session aims to provide a
cross-disciplinary view of research in the field and be inclusive to a wide
variety of work and applications (the abstract is copied below). We are
excited to have very broad support from the AGU sections of Seismology,
Study of Earth's Deep Interior, Geomagnetism, Paleomagnetism and
Electromagnetism, Hydrology, and Near Surface Geophysics:
https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session24490
We hope that this session will be of interest to you and that you and/or
your students will consider contributing an abstract.
The abstract deadline is 2 August 2017. The meeting will be held in New
Orleans, LA, from December 11-15, 2017.
Our apologies for any cross postings of this advertisement.
Best wishes,
Jan Dettmer
on behalf of the organizers:
Jan Dettmer (U Calgary)
Burke Minsley (USGS)
Anandaroop Ray (Chevron)
Vedran Lekic (U Maryland)
Thomas Bodin (U Lyon)
Kerry Key (UCSD)
Niklas Linde (U Lausanne)
Louise Pellerin (Green Geophysics)
*********************************************
Frontiers of uncertainty quantification in geoscientific inversion
Geoscientists employ inversion methods to infer Earth properties and
processes. These inferences are based on earth observations and described
by model parameters. However, incomplete and noisy observations, subjective
processing and inversion choices, non-uniqueness, and approximate physical
theory lead to parameter uncertainty. Therefore, robust interpretation of
inversion results requires uncertainty estimation, which relates parameter
knowledge to data errors. Rigorous methods for uncertainty quantification
are of great practical value across disciplines, particularly those
involving predictions, such as probabilistic hazard assessment or
hydrologic modeling. For instance, how uncertain are inferred locations of
unexploded ordnances, economic resources, or chemical contaminants? How
uncertain are tsunami predictions given uncertain earthquake rupture and
earth structure knowledge? To produce quantitative answers, inversion
methods must account for observational errors, model limitations and reduce
subjective choices. We invite submissions on all aspects of uncertainty
quantification, including theoretical advances and practical applications
across all fields of geosciences.
*********************************************
--
*Vedran Leki**ć*
Asst. Prof. Geology
Asst. Prof. Applied Mathematics & Statistics and Scientific Computation
University of Maryland, College Park
P: 301-405-4086, F: 301-314-9661
geol.umd.edu/~ved
