Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain-Reference-Cited by-同舟云学术

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Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain

Published:2016-08 Issue:8 Volume:52 Page:6643-6655
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Bracken C.¹²,Rajagopalan B.¹³,Cheng L.³⁴,Kleiber W.⁵,Gangopadhyay S.²

Affiliation:

1. Department of Civil, Environmental and Architectural EngineeringUniversity of Colorado at BoulderBoulder Colorado USA

2. Bureau of Reclamation, Technical Service CenterDenver Colorado USA

3. Cooperative Institute for Research in Environmental Sciences, University of Colorado at BoulderBoulder Colorado USA

4. NOAA Earth System Research LaboratoryBoulder Colorado USA

5. Department of Applied MathematicsUniversity of Colorado at BoulderBoulder Colorado USA

Funder

NSF

the National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2016WR018768

Reference47 articles.

1. Spatiotemporal hierarchical modelling of extreme precipitation in Western Australia using anisotropic Gaussian random fields

2. Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes

3. A region-based hierarchical model for extreme rainfall over the UK, incorporating spatial dependence and temporal trend

4. Gaussian predictive process models for large spatial data sets

5. Regional frequency analysis methods for evaluating changes in hydrologic extremes

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