White Papers
EQECAT experts have published a number of white papers addressing various topics relating to the sciences behind catastrophe modeling and natural disasters.
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Earthquake Clustering White Paper Part 1: Global Earthquakes
(PDF 2 MB)
This white paper is the first of a 3-part series on earthquake clustering. The report reviews recent scientific research that indicates we are currently in a temporal global cluster of great and giant earthquake activity. Although perhaps half-way through this current cluster, based on historical precedent, we may not have yet seen the largest earthquake to occur.
The purpose of this series is to provide perspectives on earthquake clustering in its various contexts and its implication to the seismic hazard.
Paul C. Thenhaus, Dr. Kenneth W. Campbell, and Dr. Mahmoud M. Khater authored the white paper.
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Natural Catastrophe Loss Modeling: The value of knowing how little you know
(PDF 57 KB)
Gabriela Chávez-López authored the paper that includes an introduction of major components of cat models, sources of common uncertainties in development and application of catastrophe loss models and areas for future research (hazard, vulnerability, and exposure).
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(PDF 662 KB)
Dr. Ken Campbell and Yousef Bozorgnia present a ground motion prediction equation for the horizontal component of cumulative absolute velocity (CAV) based on the PEER-NGA strong motion database.
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Activity of Catastrophic Windstorm Events in Europe in the 21st Century
(PDF 469 KB)
Using climate scenario data presented in the Intergovernmental Panel on Climate Change's (IPCC1) Special Report on Emissions Scenarios (SRES), EQECAT collaborated with experts at the Free University of Berlin to investigate the effects of climate change on extra-tropical windstorms in Europe.
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North Atlantic Hurricane Near-Term Model
(PDF 649 KB)
This white paper provides a discussion of the AMO as the basis for EQECAT's near-term model, the affect of the AMO on annual average losses, and gives an overview of the methodology used to develop the near-term model.
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Natural Hazards Damage and Financial Loss Modeling
(PDF 432 KB)
Natural hazards generate significant cumulative loss because they cover large geographical areas, a single event that can strike several countries. The settlements and impose financial issues involved in insurance and finance to quantify their exposure to such risks and in particular extreme cases. Stochastic modeling of losses provides decision makers the tools they need to simulate the complexity of the forms of existing coverage and the risk of ruin. The outline of the development of a stochastic model of floods are discussed in this white paper.
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Deterministic and Probabilistic Predictions of Yield Strength and Inelastic Displacement Spectra
(PDF 289 KB)
Dr. Ken Campbell co-authored this paper about deterministic and probabilistic predictions of inelastic response spectra based on a comprehensive ground motion prediction equation (GMPE).
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Ground Motion Prediction Equation ("Attenuation Relationship") for Inelastic Response Spectra
(PDF 4 MB)
Dr. Ken Campbell co-authored this 23-page white paper about the process and fundamental results of a comprehensive ground motion prediction equation (GMPE,or "attenuation relationship") developed for inelastic response spectra.
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A Guide to Differences between Stochastic Point-Source and Stochastic Finite-Fault Simulations
(PDF 598 KB)
Dr. Ken Campbell co-authored this paper that answers questions on the simulations of Atkinson and Boore (2006), along with other questions regarding stochastic models.
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Using Recent Hurricane Data to Evaluate Risk Models
(PDF 140 KB)
This paper discusses how natural catastrophe models have evolved to support a dynamic international property insurance industry. The paper states that these models reflect the latest understanding of science, engineering and finance to produce prospective risk evaluation tools designed to quantify the severity and volatility of natural-catastrophe linked instruments.