Not exact matches
Gary Geernaert, director of DOE's Climate and Environmental Sciences Division, states that «it is critical that federal investments to advance climate science
for use by both public and private stakeholders must place significant priority on incorporating
uncertainty quantification methodologies into modeling frameworks.
Uncertainty quantification is also a focus
for the U.S. Department of Energy (DOE) as eight national laboratories and six partner institutions collaborate to develop and apply the next generation of climate and Earth - system models to the challenges and demands of climate - change research.
This environment, designated the Virtual Environment
for Reactor Applications (VERA), incorporates science - based models, state - of - the - art numerical methods, modern computational science and engineering practices, and
uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single - effect experiments, and integral tests.
«
Uncertainty quantification» (or «UQ»
for short) is a research area that has sprung to prominence in the last decade at the interface of applied mathematics, statistics, computational science, and many applications, usually in physical sciences and engineering, but also in biology, finance, and insurance.
In this case, the committee might have discovered more than a few papers by one of them on the subject, such as Risbey and Kandlikar (2002) «Expert Assessment of
Uncertainties in Detection and Attribution of Climate Change» in the Bulletin of the American Meteorological Society, or that Prof. Risbey was a faculty member in Granger Morgan's Engineering and Public Policy department at CMU
for five years, a place awash in expert elicitation of climate (I sent my abstract to Prof. Morgan — who I know from my AGU
uncertainty quantification days —
for his opinion before submitting it to the conference).
Roy, C.J. and W.L. Oberkampf, A comprehensive framework
for verification, validation, and
uncertainty quantification in scientific computing.
The parent methodology provides definitions, applicability criteria, project boundary definition, baseline and additionality requirements,
quantification methods, monitoring and verification requirements, and
uncertainty calculations
for all modules.
Mr. Gore is careful to differentiate
uncertainties from risks, which he distinguishes
for their amenability to
quantification.
They are satisfied with the
quantification of
uncertainty, which makes a reliable basis
for engineering designs.
BTW, on an entirely different tack, while we're talking about software, there's software available
for Bayesian
uncertainty quantification and probabilistic solution of differential equations