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The statistics of extremes have played an important role in engineering practice for water resources design and management. How recent developments in the statistical theory of extreme values can be applied to improve the rigor of hydrologic applications and to make such analyses more physically meaningful is the central theme of this paper. Such… (More)

The potential advantage of extreme value theory in modeling ecological disturbances is the central theme of this paper. The statistics of extremes have played only a very limited role in ecological modeling, despite the disproportionate influence of unusual disturbances on ecosystems. An overview of this theory is provided, with emphasis on recent… (More)

- R. W. Katz
- 1999

Extreme value theory for the maximum of a time series of daily precipitation amount is described. A chain-dependent process is assumed as a stochastic model for daily precipitation, with the intensity distribution being the gamma. To examine how the eective return period for extreme high precipitation amounts would change as the parameters of the… (More)

- Adam B. Smith, Richard W. Katz
- 2013

This paper focuses on the US Billion-dollar Weather/Climate Disaster report by the National Oceanic and Atmospheric Administration’s National Climatic Data Center. The current methodology for the production of this loss dataset is described, highlighting its strengths and limitations including sources of uncertainty and bias. The Insurance Services… (More)

- Richard W. Katz
- 2009

This short course covers the application of the statistical theory of extreme values to climate, in general, and to climate change, in particular. The statistical theory of extreme values is briefly reviewed, both the extremal types theorem with its application via the block maxima approach (i.e., fitting the generalized extreme value distribution) and the… (More)

Simple stochastic models fit to time series of daily precipitation amount have a marked tendency to underestimate the observed (or interannual) variance of monthly (or seasonal) total precipitation. By considering extensions of one particular class of stochastic model known as a chain-dependent process, the extent to which this ‘‘overdispersion’’ phenomenon… (More)

- Somkiat Apipattanavis, Guillermo Podestá, Balaji Rajagopalan, Richard W. Katz
- 2007

[1] We propose a semiparametric multivariate weather generator with greater ability to reproduce the historical statistics, especially the wet and dry spells. The proposed approach has two steps: (1) a Markov Chain for generating the precipitation state (i.e., no rain, rain, or heavy rain), and (2) a k-nearest neighbor (k-NN) bootstrap resampler for… (More)

- R W Katz, S Y Teng, S Thomas, R Landesberg
- Bone
- 2002

The immediate signal-transduction response of osteoblasts to acute trauma is poorly characterized. We have developed a simple in vitro model for osteoblast trauma to investigate aspects of the molecular mechanisms of wound healing in bone. Herein we report the specific, rapid, and transient phosphorylation of extracellular signal-regulated kinase (ERK) 1… (More)

This paper introduces a framework for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. This framework is implemented in the Non-stationary Extreme Value Analysis (NEVA) software package, explicitly designed to facilitate analysis of extremes in the geosciences. In a Bayesian… (More)

- Eva M. Furrer, Richard W. Katz
- 2007

Stochastic weather generators are a popular method for producing synthetic sequences of daily weather. We demonstrate that generalized linear models (GLMs) can provide a general modeling framework, allowing the straightforward incorporation of annual cycles and other covariates (e.g. an index of the El Niño-Southern Oscillation, ENSO) into stochastic… (More)