A global perspective on past and future change in regional seasonal cycle shape

Holtanová, Eva; Koláček, Jan; Brunner, Lukas

doi:10.5194/esd-17-181-2026

Articles | Volume 17, issue 1

https://doi.org/10.5194/esd-17-181-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-17-181-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 1

Review

|

10 Feb 2026

Review |

| 10 Feb 2026

A global perspective on past and future change in regional seasonal cycle shape

Eva Holtanová, Jan Koláček, and Lukas Brunner

Supplement

https://doi.org/10.5194/esd-17-181-2026-supplement

Data sets

Underlying data and processing code accompanying the paper Holtanova et al., 2025: Quantifying changes in seasonal temperature variations using a functional data analysis approach E. Holtanová https://doi.org/10.5281/zenodo.15866119

Model code and software

Underlying data and processing code accompanying the paper Holtanova et al., 2025: Quantifying changes in seasonal temperature variations using a functional data analysis approach E. Holtanová https://doi.org/10.5281/zenodo.15866119

Interactive computing environment

Underlying data and processing code accompanying the paper Holtanova et al., 2025: Quantifying changes in seasonal temperature variations using a functional data analysis approach E. Holtanová https://doi.org/10.5281/zenodo.15866119

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Short summary

We introduce Functional Data Analysis (FDA) as a new approach to diagnose changes in the temperature seasonal cycle. FDA allows the analysis without needing any prior assumptions about the cycle shape. We evaluate past and future changes based on two reanalyses and five CMIP6 models. We discuss regions of robust changes with datasets’ agreement, e.g., a delayed maximum in the south and east of Europe, while highlighting areas of larger dataset differences, mainly in polar and equatorial regions.