Richard W. Katz

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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)
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)
[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)
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)