Statistical testing of range-size change as affected by the extremes of seasonal maximum temperatures

M. S. Dhanoa; R. Sanderson; J. L. Ellis; C. D. Powell; S. López; A. Shepherd; L. M. Cardenas; J. France

Statistical testing of range-size change as affected by the extremes of seasonal maximum temperatures

M. S. Dhanoa, R. Sanderson, J. L. Ellis, C. D. Powell, S. López, A. Shepherd, L. M. Cardenas, J. France^*

^*Corresponding author for this work

Institute of Biological, Environmental & Rural Sciences (IBERS)

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Any geo-position on Earth will have its own seasonal pattern of maximum day temperatures. Climate change driven extreme temperature episodes may disturb such patterns and create temperature range changes. The significance of such changes can be tested statistically by maximum temperature range data analysis using the distribution of the ratio of range to standard deviation. Structural pattern trends, percentiles and kurtosis summaries bring out more details of seasonal temperatures.

Original language	English
Title of host publication	Climate Change Reviews
Subtitle of host publication	2022-2024
Editors	David Hemming
Publisher	CABI Publishing
Pages	256-265
Number of pages	10
ISBN (Electronic)	9781800629486
ISBN (Print)	9781800629479
Publication status	Published - 29 Jan 2025

Keywords

Extreme value distribution
Kurtosis
Maximum temperature
Range to standard deviation ratio distribution
Split-line model
Structural patterns

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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AU - Dhanoa, M. S.

AU - Sanderson, R.

AU - Ellis, J. L.

AU - Powell, C. D.

AU - López, S.

AU - Shepherd, A.

AU - Cardenas, L. M.

AU - France, J.

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N2 - Any geo-position on Earth will have its own seasonal pattern of maximum day temperatures. Climate change driven extreme temperature episodes may disturb such patterns and create temperature range changes. The significance of such changes can be tested statistically by maximum temperature range data analysis using the distribution of the ratio of range to standard deviation. Structural pattern trends, percentiles and kurtosis summaries bring out more details of seasonal temperatures.

AB - Any geo-position on Earth will have its own seasonal pattern of maximum day temperatures. Climate change driven extreme temperature episodes may disturb such patterns and create temperature range changes. The significance of such changes can be tested statistically by maximum temperature range data analysis using the distribution of the ratio of range to standard deviation. Structural pattern trends, percentiles and kurtosis summaries bring out more details of seasonal temperatures.

KW - Extreme value distribution

KW - Kurtosis

KW - Maximum temperature

KW - Range to standard deviation ratio distribution

KW - Split-line model

KW - Structural patterns

UR - http://www.scopus.com/inward/record.url?scp=85219582886&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:85219582886

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SP - 256

EP - 265

BT - Climate Change Reviews

A2 - Hemming, David

PB - CABI Publishing

ER -

Statistical testing of range-size change as affected by the extremes of seasonal maximum temperatures

Abstract

Keywords

UN SDGs

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Statistical testing of range-size change as affected by the extremes of seasonal maximum temperatures

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