Heatwaves as Extreme Events
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[34] emphasized the theoretical underpinnings of extreme value distributions, including the GPD, highlighting its utility in characterizing the intensity and frequency of heatwaves as statistically rare and physically impactful phenomena.
“Similarly, [34] emphasized the theoretical underpinnings of extreme value distributions, including the GPD, highlighting its utility in characterizing the intensity and frequency of heatwaves as statistically rare and physically impactful phenomena.”
From Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs (2024) · cites this paper as [34]
The Generalized Pareto Distribution is a cornerstone of extreme value theory and is well-suited for modeling the tails of distributions to predict rare and extreme events such as heatwaves.
“The Generalized Pareto Distribution (GPD) is a cornerstone of extreme value theory, particularly well-suited for modeling the tails of distributions to predict rare and extreme events such as heatwaves.”
From Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs (2024) · cites this paper as [34]
Cites
A review of quantification methodologies for multi-hazard interrelationships
Tilloy, A., Malamud, B. D., Winter, H., & Joly-Laugel, A. (2019) · Earth-Science Reviews · doi:10.1016/j.earscirev.2019.102881 · Cited by 364 · see citing works
Exposure, instrumentation, and observing practice effects on land temperature measurements
Trewin, B. (2010) · WIREs Climate Change · doi:10.1002/wcc.46 · Cited by 153 · see citing works
Rennie, J. J., Lawrimore, J. H., Gleason, B. E., Thorne, P. W., Morice, C. P., Menne, M. J., Williams, C. N., de Almeida, W. G., Christy, J. R., Flannery, M., et al. (2014) · Geoscience Data Journal · doi:10.1002/gdj3.8 · Cited by 123 · see citing works
Future projections of heat waves over India from CMIP5 models
Rohini, P., Rajeevan, M., & Mukhopadhay, P. (2019) · Climate Dynamics · doi:10.1007/s00382-019-04700-9 · Cited by 120 · see citing works
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Chishtie, F. A., Brunet, D., White, R. H., Michelson, D., Jiang, J., Lucas, V., Ruboonga, E., Imaash, S., Westland, M., Chui, T., et al. (2024) · arXiv · doi:10.48550/arxiv.2411.13496
- Authors
- McGregor, G.
- Affiliations
- Durham University (GB)
- Corresponding author
- McGregor, Glenn
- ORCID
- McGregor, Glenn
- Venue
- Biometeorology
- Publisher
- Springer International Publishing
- Published
- 2024
- Pages
- 81-133
- ISSN
- 1877-5284 (ISSN-L)
- 2452-1558
- OpenAlex
- W4403255394
- Cited by
- 1
- References
- 4
- Citations by year
- 2026: 1
- FWCI
- 1.34
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Biometeorology (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
- Keywords
- heat waves, extreme events, climate extremes, heat wave definition, social vulnerability, extreme value theory, generalized extreme value distribution, generalized Pareto distribution, climate data sources, climate reanalysis, climate model output
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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.
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