CONTROL ID: 1478219

TITLE: Analysis and Intercomparison of CMIP5 Models Using Clustered Climate Regimes

AUTHORS (FIRST NAME, LAST NAME): Eva Sinha1, Jitendra Kumar2, Forrest M Hoffman2

INSTITUTIONS (ALL): 1. Paul C Rizzo Associates, Albany, CA, United States.
2. Oak Ridge National Laboratory, Oak Ridge, TN, United States.

ABSTRACT BODY: Coupled Earth System Models (ESMs) simulate the Earth’s climate and biogeochemical responses to changes in environmental conditions driven by anthropogenic greenhouse gas emissions. A range of future emissions scenarios, called Representative Concentration Pathways (RCPs), prepared for the fifth phase of the Climate Model Intercomparison Project (CMIP5), were employed as forcings for global climate simulations contributed to the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Routine assessment of model-projected changes in the hydrological cycle under various climate change scenarios is necessary to understand possible impacts on natural ecosystems, water resources, and future carbon dioxide concentrations, and to plan adaptation strategies. We have applied a highly scalable data mining algorithm as a component of statistical analyses to results of model simulations that used these RCPs as forcings. These statistical methods were used to identify salient features of projected changes in the global hydrological cycle from multiple CMIP5 models using multiple RCPs. Dynamics of clustered climate regimes through time, which provide insights into changing water resources availability and distributions under climate change scenarios, will be presented.

KEYWORDS: [1910] INFORMATICS / Data assimilation, integration and fusion, [1914] INFORMATICS / Data mining, [1932] INFORMATICS / High-performance computing, [1986] INFORMATICS / Statistical methods: Inferential.
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CONTACT (E-MAIL ONLY):sinha_e at yahoo dot com