The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Definition, diagnosis, and origin of extreme weather and climate events
Abstract
Condensed summary Extreme weather and climate events are a major source of risk for all human societies. There is a pressing need for more research on such events. Various societal changes, such as increased populations in coastal and urban areas and increasingly complex infrastructure, have made us potentially more vulnerable to such events than we were in the past. In addition, the properties of extreme weather and climate events are likely to change in the twenty-first century owing to anthropogenic climate change. The definition, classification, and diagnosis of extreme events are far from simple. There is no universal unique definition of what is an extreme event. This chapter discusses these issues and presents a simple framework for understanding extreme events that will help enable future work in this important area of climate science and global reinsurance. Introduction Human society is particularly vulnerable to severe weather and climate events that cause damage to property and infrastructure, injury, and even loss of life. Although generally rare at any particular location, such events cause a disproportionate amount of loss. In this chapter, I attempt to describe a framework for classifying, diagnosing, and understanding extreme weather and climate events. The multidimensional aspect of complex extreme events will be discussed, and statistical methods will be presented for understanding simple extreme events. Some preliminary ideas about the origin of extreme events will also be presented. Definition of extreme events Extreme events are generally easy to recognize but difficult to define. This is due to several reasons.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An Introduction to Statistical Modeling of Extreme Values
Coles, S. (2001) · Springer Series in Statistics · doi:10.1007/978-1-4471-3675-0 · Cited by 7,352
Cited by
Defining Extreme Events: A Cross‐Disciplinary Review
McPhillips, L. E., Chang, H., Chester, M. V., Depietri, Y., Friedman, E., Grimm, N. B., Kominoski, J. S., McPhearson, T., Méndez‐Lázaro, P., Rosi, E. J., et al. (2018) · Earth's Future · doi:10.1002/2017ef000686 · Cited by 317
Forecast verification: Current status and future directions
Casati, B., Wilson, L. J., Stephenson, D. B., Nurmi, P., Ghelli, A., Pocernich, M., Damrath, U., Ebert, E. E., Brown, B. G., & Mason, S. (2008) · Meteorological Applications · doi:10.1002/met.52 · Cited by 306
Self-citationCruz, J., White, P. C. L., Bell, A., & Coventry, P. A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17228581 · Cited by 147
Extreme weather-driven disasters and children's health
Garcia, D. M., & Sheehan, M. C. (2016) · International Journal of Health Services · doi:10.1177/0020731415625254 · Cited by 98
Bauer, T., Ingram, V., De Jong, W., & Arts, B. (2018) · International Forestry Review · doi:10.1505/146554818824063050 · Cited by 23
Metadata
- Authors
- Stephenson, D. B.
- Venue
- Climate Extremes and Society
- Publisher
- Cambridge University Press
- Published
- 2008-05-22
- Pages
- 11-23
- OpenAlex
- W2095960900
- Cited by
- 169
- References
- 1
- FWCI
- 1.38
- Type
- book chapter
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Definition, diagnosis, and origin of extreme weather and climate events. https://app.cochat.ai/papers/10.1017/cbo9780511535840.004
- The paper
- Stephenson, D. B. (2008). Definition, diagnosis, and origin of extreme weather and climate events. Climate Extremes and Society. https://doi.org/10.1017/cbo9780511535840.004
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.