GC31F:
Interpretation and Uncertainty in Climate, Earth System, Integrated Assessment, and Impact Models and Observations I Posters

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Session ID#: 12924

Session Description:
Interpreting climate simulations, associated observational data, and assessing their uncertainties are essential to understanding changes in atmospheric, land, oceanic, and socio-economic systems and processes. Quantified uncertainty is needed to identify human-induced causes of climate change, to attribute the occurrence of extreme weather events to anthropogenic factors as well as to predict the impact of the evolving polar climate. We seek contributions in model interpretation, evaluation of models against observations, as well as studies that identify, quantify, or interpret uncertainty in climate models and/or observations. Contributions may address models and observations at multiple spatial and temporal scales. We welcome all studies that use these models in forecasting, sensitivity analyses, data assimilation and statistical inverse problems.
Primary Convener:  Elisabeth A Lloyd, Indiana University Bloomington, History and Philosophy of Science and Medicine, Bloomington, IN, United States
Conveners:  Jaideep Ray, Sandia National Laboratories, Albuquerque, NM, United States, Donald D Lucas, Lawrence Livermore National Laboratory, Livermore, CA, United States and Maoyi Huang, Pacific Northwest National Laboratory, Atmospheric Sciences and Global Change Division, Richland, WA, United States
Chairs:  Jaideep Ray, Sandia National Laboratories, Albuquerque, NM, United States, Maoyi Huang, Pacific Northwest National Laboratory, Atmospheric Sciences and Global Change Division, Richland, WA, United States, Donald D Lucas, Lawrence Livermore National Laboratory, Livermore, CA, United States and Elisabeth A Lloyd, Indiana University Bloomington, History and Philosophy of Science and Medicine, Bloomington, IN, United States
OSPA Liaison:  Jaideep Ray, Sandia National Laboratories, Albuquerque, NM, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • EP - Earth and Planetary Surface Processes
  • PP - Paleoceanography and Paleoclimatology
  • SI - Societal Impacts and Policy Sciences
Index Terms:

0550 Model verification and validation [COMPUTATIONAL GEOPHYSICS]
1622 Earth system modeling [GLOBAL CHANGE]
1626 Global climate models [GLOBAL CHANGE]
1990 Uncertainty [INFORMATICS]

Abstracts Submitted to this Session:

Non-robust numerical implementations impact global carbon and water cycle simulations: a demonstration with two ESM land models (136656)
Jinyun Tang and William J Riley, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere (136811)
Cheng-En Yang1,2, Jiafu Mao3, Dr. Forrest M Hoffman, PhD2, Daniel M Ricciuto2 and Joshua S Fu4,5, (1)University of Tennessee, Civil and Environmental Engineering, Knoxville, TN, United States, (2)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (4)University of Tennessee, Civil and Environmental Engineering, Knoxville, United States, (5)Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, United States
Comparing Natural and Economic Carbon Cycle Feedbacks (194191)
Dawn Woodard1, Weiwei Fu2, Steven J Davis3 and James Tremper Randerson1, (1)University of California Irvine, Earth System Science, Irvine, CA, United States, (2)University of California Irvine, Department of Earth System Science, Irvine, CA, United States, (3)University of California, Irvine, Irvine, CA, United States
Is Time the Best Metric to Measure Carbon-Related Climate Change Potential and Tune the Economy Toward Reduced Fossil Carbon Extraction? (198978)
Forrest A DeGroff, City College of San Francisco, San Francisco, CA, United States
UQ Analysis of the Double ITCZ Problem (165776)
Gemma Jayne Anderson and Donald D Lucas, Lawrence Livermore National Laboratory, Livermore, CA, United States
Reducing Errors in Satellite Simulated Views of Clouds with an Improved Parameterization of Unresolved Scales (177323)
Benjamin R Hillman, Sandia National Laboratories, Albuquerque, NM, United States, Roger Marchand, Applied Physics Laboratory University of Washington, Seattle, WA, United States and Thomas P Ackerman, Joint Institute for the Study of the Atmosphere and Ocean, Seattle, WA, United States
Information Criterion Comparison of Two Deep Convection Ensembles in the ACME Climate Model (166813)
Donald D Lucas1, Gemma Jayne Anderson1, Vera Bulaevskaya1, Kenny Chowdhary2, Bert Debusschere3 and Steven John Ghan4, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)Sandia National Laboratories, Albuquerque, NM, United States, (3)Sandia National Laboratories, Livermore, CA, United States, (4)Pacific Northwest National Laboratory, Richland, WA, United States
Using multi-chain Markov chain Monte Carlo methods to calibrate geoscientific models (137769)
Jaideep Ray, Sandia National Laboratories, Albuquerque, NM, United States, Laura Swiler, Sandia National Laboratories, Albuquerque, United States, Jie Bao, Pacific Northwest National Laboratory, Richland, WA, United States, Zhangshuan Hou, Pacific Northwest National Laboratory, Energy and Environment Directorate, Richland, WA, United States and Maoyi Huang, Pacific Northwest National Laboratory, Atmospheric Sciences and Global Change Division, Richland, WA, United States
Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines (161987)
Devin Francom1, Bruno Sansó2, Vera Bulaevskaya1 and Donald D Lucas1, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)University of California Santa Cruz, Statistics, Santa Cruz, CA, United States
Are quantitative sensitivity analysis methods always reliable? (168930)
Xin Huang, Tsinghua University, Beijing, China
Reducing the Uncertainty in Atlantic Meridional Overturning Circulation Projections Using Bayesian Model Averaging (154483)
Roman Olson, Yonsei University, Seoul, Korea, Republic of (South) and Soon-Il An, Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
Validation of Sea Ice Models Using an Uncertainty-Based Distance Metric for Multiple Quantities of Interest (189765)
Jorge Rolando Urrego-Blanco, Los Alamos National Laboratory, Los Alamos, United States and Nathan M Urban, Los Alamos National Laboratory, Los Alamos, NM, United States
Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate (150484)
Ben P Bond-Lamberty1, Andrew D Jones2, Xiaoying Shi3 and Katherine V Calvin1, (1)Pacific Northwest National Laboratory, Joint Global Change Research Institute, Richland, WA, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (3)Oak Ridge National Laboratory, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge, TN, United States
No Spatial Analogue – Novel Climates and Disappearing Climates (175222)
Fabienne Dahinden, Erich M Fischer and Reto Knutti, ETH Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
Climate Observing System Simulation Experiments: Reducing the Uncertainty in Climate Uncertainty (186388)
Elizabeth C Weatherhead, U. Colorado at Boulder, Boulder, CO, United States, Bruce A Wielicki, NASA Langley Research Center, Hampton, VA, United States and V Ramaswamy, NOAA/OAR/ GFDL, Princeton, United States
Probabilistic Estimates of Climate Impacts of the Paris Agreement (142391)
Andrei P Sokolov1, Sergey Paltsev2, Henry Chen1, Chris E Forest3, Alex G Libardoni4, Erwan Monier5 and Xiang Gao6, (1)Massachusetts Institute of Technology, Joint Program on the Science and Policy of Global Change, Cambridge, MA, United States, (2)Massachusetts Institute of Technology, Center for Sustainability Science and Strategy, Cambridge, United States, (3)Pennsylvania State University Main Campus, Meteorology and Atmospheric Science, University Park, PA, United States, (4)Pennsylvania State University Main Campus, Meteorology, University Park, PA, United States, (5)University of California Davis, Department of Land, Air & Water Resources, Davis, CA, United States, (6)Massachusetts Institute of Technology, Cambridge, MA, United States
Evaluation of Climate Model Output Against Observations in a Hypothesis Testing Framework (199360)
Brandi M Quam, NASA Langley Research Center, Hampton, VA, United States and Amy J Braverman, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
What can we gain by using Bayesian methods to combine information from a multi-model ensemble? (194696)
Alexandra K Jonko and Nathan M Urban, Los Alamos National Laboratory, Los Alamos, NM, United States
Model Independence in Downscaled Climate Projections: a Case Study in the Southeast United States (184152)
Geneva Gray and Ryan Boyles, North Carolina State University Raleigh, Raleigh, NC, United States
Signal to noise quantification of regional climate projections  (188739)
Sihan Li, Oregon State University, Corvallis, OR, United States, David E Rupp, Oregon Climate Change Research Institute, CEOAS/OSU, Corvallis, OR, United States and Philip Mote, Oregon Climate Change Research Institute, Corvallis, OR, United States
Downscaled Projections of 21st Century Bioclimatic Variables for U.S. Climate Divisions (199666)
Robert Nicholas, Pennsylvania State University Main Campus, Earth and Environmental Systems Institute, University Park, PA, United States
Can climate models be tuned to simulate the global mean absolute temperature correctly? (153269)
Qingyun Duan, Hohai University, Nanjing, China, Yuhan Shi, Beijing Normal University, Beijing, China and Wei Gong, Beijing Normal University, Institute of Land Surface System and Sustainable Development, Faculty of Geographical Sciences, Beijing, China
Trends and associated uncertainty in the global mean temperature record (198491)
Andrew N Poppick, Carleton College, Mathematics and Statistics, Northfield, MN, United States, Elisabeth J Moyer, University of Chicago, Department of the Geophysical Sciences, Chicago, United States and Michael Stein, University of Chicago, Department of Statistics, Chicago, IL, United States

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