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Abstract Details
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Activity Number:
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303
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #306802 |
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Title:
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Bivariate Spatio-Temporal Modeling for the Hydrological Cycle of the Central United States
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Author(s):
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Jonathan Hobbs*+
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Companies:
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Iowa State University
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Address:
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2804 Stange Road, Ames, IA, 50010-4019, United States
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Keywords:
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precipitation ;
spatial statistics ;
meteorology ;
spatio-temporal model ;
hierarchical model
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Abstract:
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Environmental variables are often linked by basic conservation laws that characteristic sources and sinks for particular quantities. These simple relationships can be incorporated into stochastic models for the space-time variation of multiple variables. This work uses the water vapor budget to link atmospheric water vapor transport and precipitation over the central United States during the summer season. A bivariate spatio-temporal model is developed that incorporates important characteristics of these fields; including a spatially-varying low-amplitude diurnal cycle, strong regional-scale relationships between the fields that change with time, and local spatial and cross-variable dependence. These components are linked conditionally in a hierarchical model, and Bayesian analysis is illustrated for a multi-year dataset from a combination of sources.
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