[Faculty] Fwd: [CSRC.COLLOQUIUM] "Projecting the Future: Quantifying Uncertainties in How the Climate Will Change "

[Jose Castillo]

*[image: SDSU_CSRC Logo.jpg]*


***** Registration is required in order to get the link to join the seminar
online. Please register at the below web page.*


DATE:
*Friday, November 4, 2022*


TITLE:
*Projecting the Future: Quantifying Uncertainties in How the Climate Will
Change*
VIEWING PARTY
GMCS 314

TIME:
*3:30-5:00PM*



LOCATION:
*Registration is required in advance.  Please register at the following
site to receive information on how to join the seminar online.   *Meeting
Registration - Zoom
<https://us06web.zoom.us/meeting/register/tZwkfuqoqj8qGdAgXuaIPOUkdDgiRREhBmq7>



SPEAKER/BIO:
*Dr.* *Nathan Urban, Applied Mathematics, Brookhaven National Laboratory *



ABSTRACT:
As carbon dioxide emissions to the atmosphere continue from fossil fuel
consumption, the Earth's climate will change considerably over the course
of this century due to the resulting greenhouse effect. Societies and
ecosystems will feel these global changes in the form of extreme weather,
recurrent flooding and droughts, and other regional impacts. But how
certain are we in projections about the distant future? Every prediction of
a physical theory comes with error bars arising from limitations in data
and approximations that are made for the sake of computational
tractability. The scientific question is not whether the climate will
change, but how likely it is to change by a given amount. This talk will
discuss at a conceptual level the general mathematical formalism of
statistical uncertainty quantification, and how it is being applied within
the U.S. Department of Energy and other research institutions to estimate
the plausible range of possible climate futures. The mathematical methods
discussed may include Bayesian parameter estimation for nonlinear
regression, Monte Carlo sampling, sensitivity analysis, model averaging,
and surrogate modeling or emulation of expensive computer simulations.
Applications may include probabilistic predictions of global warming and
climate feedbacks, sea level rise from Antarctic ice sheet disintegration,
and coastal flooding, among others. As time permits, I will also discuss
educational training and career paths into this research field at the
forefront of interdisciplinary science.

Bio:  Dr. Nathan Urban leads the Applied Mathematics group in the
Computational Science Initiative at Brookhaven National Laboratory, on Long
Island, New York. He received undergraduate degrees in physics, computer
science, and mathematics from Virginia Tech, and a Ph.D. and M.Ed. in
physics (computational statistical mechanics) from Penn State. After
graduating, he moved into climate uncertainty quantification with
postdoctoral appointments at Penn State and Princeton, and a staff position
at Los Alamos National Laboratory. He received a DOE Office of Science
Early Career Research award for multi-model climate uncertainties, and has
led major projects involving coastal resilience planning under uncertainty
and "in-situ" methods for embedding scalable statistical inference
algorithms within exascale simulations. At Brookhaven he develops
methodologies for uncertainty quantification, decision making under
uncertainty and optimal experimental design, model reduction, scientific
machine learning, and integrated computational frameworks for decision
support, applied to problems in climate science, biomedicine, materials
science, and others.


Host:
*Ignacio Sepulveda (Engineering) and the Sustainable Horizons Institute
CRLC Virtual Seminar Series  *


Note: Videos of previous colloquium talks can be seen on the CSRC website
in the colloquium archive section or on the CSRC YouTube page here
<https://www.youtube.com/channel/UCN0ZEztlmyDqG2pm-Rle_Eg/feed>.

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