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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 REGIONALMODELS AND MULTI-MODEL ENSEMBLES8:30 Ralph Milliff – A tale of two Bayesian hierarchical models: Uncertainty estimation in models and datasets for large state-space geophysical applications9:05 Bruno Sanso – Assessing regional climate model predictions9:40 Veronica J. Berrocal – Regional climate model assessment using statistical upscaling and downscaling techniques10:15 Yangang Liu – Building a multiscale data framework for evaluating fast physics in climate models10:30-10:45 Break10:45-12:00 SESSION 4 – CLIMATE IMPACTS STUDIES10:45 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, USA11:15 Deepak Ray – Changes to global crop production from recent climate trends11:30 Jane R. Foster – Sensitivity of tree, species and stand biomass growth to summer water deficits from tree-ring reconstructions in northern Minnesota11:45 Discussion12:00-1:00 Lunch1:00-3:00 SESSION 5 – FRAMEWORKS FOR PARTITIONING UNCERTAINTY INSPATIO-TEMPORAL DATA1:00 Sudipto Banerjee – Statistical inference for space-time gradients under process-based settings1:35 Cindy L. Bruyere – Evaluating sources of uncertainty in regional climate models2:10 Joseph Guinness – Nonstationary spatial-temporal statistical models for regional weather model output2:45 Yang Li – Modeling nonstationary covariance function on spheres with convolution3:00-3:15 Break3:15-4:30 Group(s) process toward identifying working groups4:30-6:00 Poster session