Seasonality as a core business of phenology

Jeanneret, François; Rutishauser, This (2010). Seasonality as a core business of phenology. In: Keatley, Marie; Hudson, Irene (eds.) Phenological Research: methods for environmental and climate change analysis (pp. 63-74). Heidelberg: Springer Verlag 10.1007/978-90-481-3335-2_3

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The best characteristics of phenological observations are their description of seasons and seasonal patterns. Specific phenological phases are used to define the beginning and the end of seasons that form phenological calendars. Phenological observations more closely capture the integrated seasonal rhythm than statistically derived means or thresholds from climate elements. They only provide approximate indicators of seasonal changes and cannot replace visible or directly measurable phenomena. Including abiotic observations such as the timing of frost, thawing, icing, snow and fog even provides seasonality descriptions beyond the vegetation period. The length and position of seasons within the year is a foundation for an integrated description of seasonality presented as a phenological season diagram. Phenological observations are the indispensable basis for an integral description of a seasonal classification and seasonality. A well designed phenological diagram could offer a comprehensive picture of the rhythm and amplitude of seasons.

Item Type:

Book Section (Book Chapter)

Division/Institute:

08 Faculty of Science > Institute of Geography > Physical Geography
08 Faculty of Science > Institute of Geography > Physical Geography > Unit Climatology
08 Faculty of Science > Institute of Geography

UniBE Contributor:

Jeanneret, François, Rutishauser, This

Subjects:

900 History > 910 Geography & travel

ISBN:

978-90-481-3334-5

Publisher:

Springer Verlag

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:20

Last Modified:

05 Dec 2022 14:05

Publisher DOI:

10.1007/978-90-481-3335-2_3

BORIS DOI:

10.7892/boris.6417

URI:

https://boris.unibe.ch/id/eprint/6417 (FactScience: 211381)

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