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Trends and spatial pattern recognition of warm season hot temperatures in Saudi Arabia

  • Ali S. AlghamdiEmail author
  • John HarringtonJr
Original Paper

Abstract

Temporal trends and spatial patterns of six warm season (May–September) hot temperature indicators (WSHTIs) were developed and explored for Saudi Arabia. The indicators focus on the frequency and intensity of hot days and nights, and heat waves. Systematic upward trends in maximum (Tmax) and minimum (Tmin) temperatures were found at most of the stations, suggesting ongoing change in the climatology of the upper-tail of the frequency distribution. Taking into the account the observed effects of climate change on the country’s climate, hot temperature events were defined using a monthly and decadal, time-sensitive approach. Indicators of event frequency are count data; thus, different Poisson models were used for temporal analysis. Further, a novel method of time-series clustering was introduced to recognize spatiotemporal patterns of WSHTIs. Different patterns were observed over time and space not only across stations but also among WSHTIs. Generally, warming trends were detected in the upper limits for both Tmax and Tmin across the warm season months with a few surprising exceptions, mostly for Tmax. Results suggest that the impact of climate change on hot weather events was more pronounced at night at most of the stations in Saudi Arabia. The overall results suggest that not only local and regional factors, such as elevation, latitude, and distance from a large body of water, but also large-scale factors such as atmospheric circulation patterns are likely responsible for the observed temporal and spatial patterns.

Keywords

Hot temperature indicators Time-sensitive approach Spatial pattern recognition Time-series clustering Poisson models Saudi Arabia 

Notes

Acknowledgments

The authors acknowledge the freely available statistical software: R (http://www.r-project.org/).

Funding information

This work is a part of first author’s doctoral dissertation research at Kansas State University, where the first author was sponsored by King Saud University. The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Thesis Publication Fund No (TPF-009).

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Geography, College of ArtKing Saud UniversityRiyadhKingdom of Saudi Arabia
  2. 2.Department of GeographyKansas State UniversityManhattanUSA

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