The parameter optimization problem in state-of-the-art climate models and network analysis for systematic data mining in
The focus of this work is on two major problems facing the scientific community when using increasingly complicated climate model outputs to investigate the past and future evolution of our climate. On one hand, it is important to assess the reliability o
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Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA ‡ College of Computing, Georgia Institute of Technology, Atlanta, GA, USA § Dept. of Atmospheric and Oceanic Sciences, UCLA, Los Angeles, USA Abstract The focus of this work is on two major problems facing the scientific community when using increasingly complicated climate model outputs to investigate the past and future evolution of our climate. On one hand, it is important to assess the reliability of such models and how their response to increased greenhouse gas concentrations may depend on the parameters and parameterizations chosen; on the other, it is fundamental to improve our ability to validate and compare model results in a robust, compact, and meaningful way. Understanding how sensitive climate models are to changes in their parameters is of fundamental importance when addressing the problem of modeled climate sensitivity. Here a quadratic metamodel that uses a polynomial approximation to describe the parameter dependency is presented together with its application to the Community Atmospheric Model, CAM, in its two latest versions. Furthermore, the application of complex network analysis to climate fields is briefly summarized and a novel methodology that allows for robust model intercomparisons is presented together with a set of metrics to quantify the topological properties of model outputs. The application of the network analysis to outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) completes the notes.
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The authors wish to thank the generous support of the US Department of Energy through the SciDAC program, DE-SC0007143, and of the National Science Foundation, grant DMS 1049095 that supported this work.
A. Provenzale et al. (Eds.), The Fluid Dynamics of Climate, CISM International Centre for Mechanical Sciences DOI 10.1007/ 978-3-7091-1893-1_5 © CISM Udine 2016
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Introduction
General circulation models currently used for understanding current and past climate and for predicting its evolution in the future, exhibit substantial spreads in their equilibrium sensitivity, implying that the magnitude of their temperature increase in response to a doubling carbon dioxide is uncertain. The mean temperature increase over the 21st century projected by models in the last Intergovernmental Panel on Climate Change assessment continues to resist any narrowing of the range of estimates even in the historical integrations (1; 2), while the evolution of the major modes of variability of the climate system diverges (3; 4). Large uncertainties for end-of-century climatic variables prevails not only in the simulation of future surface-air temperatures, but also in precipitation (5), cloud cover (6; 7), winds (8), sea level (9), sea ice (10), and other variables of importance for socio-economic, ecological and human-health impacts. It is fair to state that while no legitimate doubts exist about the future rise
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