Douglas Nychka

Director, Institute of Mathematics Applied to Geosciences (IMAGe) at the National Center for Atmospheric Research, Boulder, Colorado

Title- Large and non-stationary spatial fields: Quantifying uncertainty in
 climate models (slides)

Douglas Nychka, National Center for Atmospheric Research

Abstract- This work is a substantive application of data science to the analysis
of climate model experiments. Pattern scaling has proved to be a
useful way to extend and interpret Earth system model (i.e. climate)
simulations. In the simplest case the response of local temperatures
is assumed to be a linear function of the global temperature. This
relationship makes it possible to consider many different scenarios of
warming by using a simpler, global climate model and combining them
with the scaling pattern from a more complex model. This work explores
methodologies using spatial statistics to quantify how the pattern
varies across an ensemble of model runs. The key is to represent the
pattern uncertainty as a Gaussian process with a spatially varying
covariance function. When applied to the NCAR/DOE CESM1 large ensemble
experiment this approach can reproduce the heterogenous variation of
the pattern among ensemble members .  The climate model output at one
degree resolution has more than 50,000 spatial locations. The size of
these "big data" break conventional spatial methods and so motivates
the development of approximate methods that are computationally
feasible. A fixed-rank Kriging model (LatticeKrig) exploiting Markov
random fields is presented that gives a global representation of the
covariance function on the sphere and provides a route to quantifying
the uncertainty in the pattern.  Much of the local statistical
computations are embarrassingly parallel and the analysis can be
accelerated by parallel tools within the R statistical environment.
 

Biography

Douglas Nychka is a statistician and data scientist whose areas of research include the theory, computation and application of curve and surface fitting with a focus on geophysical and environmental applications.  Currently he is Director, Institute of Mathematics Applied to Geosciences (IMAGe) at the National Center for Atmospheric Research, Boulder, Colorado.  Starting in Fall 2018 he will join the Department of Applied Mathematics and Statistics at the Colorado School of Mines. His current interests are in quantifying the uncertainty of numerical experiments that simulate the Earth's present and future climates. He also has an interest in combining high performance computing and R for the analysis of large spatial data sets.

Douglous Nychka