July 15-19, 2013
Mesa Laboratory, Main Seminar Room.
Sessions will be webcast : http://www.fin.ucar.edu/it/mms/ml-live.htm
This workshop will bring together statistical and data scientists with those modeling climate and climate impacts to share ideas on improving the creation of data products.
8:30-10:30 SESSION 3 – UNCERTAINTY QUANTIFICATION IN REGIONAL
MODELS AND MULTI-MODEL ENSEMBLES
8:30 Ralph Milliff – A tale of two Bayesian hierarchical models: Uncertainty estimation in models and datasets for large state-space geophysical applications
9:05 Bruno Sanso – Assessing regional climate model predictions
9:40 Veronica J. Berrocal – Regional climate model assessment using statistical upscaling and downscaling techniques
10:15 Yangang Liu – Building a multiscale data framework for evaluating fast physics in climate models
10:45-12:00 SESSION 4 – CLIMATE IMPACTS STUDIES
10:45 Colin M. Beier – Mapping climate change with high-resolution data - untapped opportunity or caveat emptor?
11:00 David M. Bell – Examining spatial variation in tree species occupancy responses to climate in Colorado, USA
11:15 Deepak Ray – Changes to global crop production from recent climate trends
11:30 Jane R. Foster – Sensitivity of tree, species and stand biomass growth to summer water deficits from tree-ring reconstructions in northern Minnesota
1:00-3:00 SESSION 5 – FRAMEWORKS FOR PARTITIONING UNCERTAINTY IN
1:00 Sudipto Banerjee – Statistical inference for space-time gradients under process-based settings
1:35 Cindy L. Bruyere – Evaluating sources of uncertainty in regional climate models
2:10 Joseph Guinness – Nonstationary spatial-temporal statistical models for regional weather model output
2:45 Yang Li – Modeling nonstationary covariance function on spheres with convolution
3:15-4:30 Group(s) process toward identifying working groups
4:30-6:00 Poster session