Spatial Hierarchical Modeling of Precipitation Extremes From a Regional Climate Model

@inproceedings{Daniel2010SpatialHM,
  title={Spatial Hierarchical Modeling of Precipitation Extremes From a Regional Climate Model},
  author={Daniel and Danielle Cooley and R{\"u}diger Stephan and SAIN},
  year={2010}
}
The goal of this work is to characterize the extreme precipitation simulated by a regional climate model (RCM) over its spatial domain. For this purpose, we develop a Bayesian hierarchical model. Since extreme value analyses typically only use data considered to be extreme, the hierarchical approach is particularly useful as it sensibly pools the limited data from neighboring locations. We simultaneously model the data from both a control and future run of the RCM which allows for easy… CONTINUE READING
Highly Cited
This paper has 67 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

67 Citations

01020'10'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 67 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 27 references

Generalized Maximum-Likelihood Generalized Extreme-Value Quantile Estimators for Hydrologic Data,

  • E. Martins, J. Stedinger
  • Water Resources Research,
  • 2000
Highly Influential
14 Excerpts

Statistical Inference Using Extreme Order Statistics,

  • J. Pickands
  • Annals of Statistics,
  • 1975
Highly Influential
6 Excerpts

spam: SPArse Matrix,

  • R. Furrer
  • R package version
  • 2008
Highly Influential
4 Excerpts

Hierarchical Modeling and Analysis for Spatial Data

  • S. Banerjee, B. Carlin, A. Gelfand
  • Monographs on Statistics and Applied Probability…
  • 2004
Highly Influential
4 Excerpts