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

doi:10.1079/cabireviews.2023.0009

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: Contribution to journal › Review Article › peer-review

1 Citation (Scopus)

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
Journal	CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources
Volume	2023
DOIs	https://doi.org/10.1079/cabireviews.2023.0009
Publication status	Published - 16 Mar 2023

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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Dhanoa, M. S., Sanderson, R., Ellis, J. L., Powell, C. D., López, S., Shepherd, A., Cardenas, L. M., & France, J. (2023). Statistical testing of range-size change as affected by the extremes of seasonal maximum temperatures. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2023. https://doi.org/10.1079/cabireviews.2023.0009

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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.",

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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.

PY - 2023/3/16

Y1 - 2023/3/16

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

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U2 - 10.1079/cabireviews.2023.0009

DO - 10.1079/cabireviews.2023.0009

M3 - Review Article

AN - SCOPUS:85151727969

SN - 1749-8848

VL - 2023

JO - CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources

JF - CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources

ER -

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

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Keywords

UN SDGs

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