What we talk about when we talk about seasonality – A transdisciplinary review

• Published in: Earth-Science Reviews
• Main Authors: Kwiecien, O., Braun, T., Brunello, C., Faulkner, P., Hausmann, N., Helle, G., Hoggarth, J., Ionita, M., Jazwa, C., Kelmelis, S., Marwan, N., Nava-Fernandez, C., Nehme, C., Opel, T., Oster, J., Perşoiu, A., Petrie, C., Prufer, K., Saarni, S., Wolf, A., Breitenbach, S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Ice; permafrost
• Online Access: https://publications.pik-potsdam.de/pubman/item/item_26857; https://publications.pik-potsdam.de/pubman/item/item_26857_1/component/file_26858/Braun+etal_2022Seasonality.pdf

The role of seasonality is indisputable in climate and ecosystem dynamics. Seasonal temperature and precipitation variability are of vital importance for the availability of food, water, shelter, migration routes, and raw materials. Thus, understanding past climatic and environmental changes at seasonal scale is equally important for unearthing the history and for predicting the future of human societies under global warming scenarios. Alas, in palaeoenvironmental research, the term ‘seasonality change’ is often used liberally without scrutiny or explanation as to which seasonal parameter has changed and how. Here we provide fundamentals of climate seasonality and break it down into external (insolation changes) and internal (atmospheric CO2 concentration) forcing, and regional and local and modulating factors (continentality, altitude, large-scale atmospheric circulation patterns). Further, we present a brief overview of the archives with potentially annual/seasonal resolution (historical and instrumental records, marine invertebrate growth increments, stalagmites, tree rings, lake sediments, permafrost, cave ice, and ice cores) and discuss archive-specific challenges and opportunities, and how these limit or foster the use of specific archives in archaeological research. Next, we address the need for adequate data-quality checks, involving both archive-specific nature (e.g., limited sampling resolution or seasonal sampling bias) and analytical uncertainties. To this end, we present a broad spectrum of carefully selected statistical methods which can be applied to analyze annually- and seasonally-resolved time series. We close the manuscript by proposing a framework for transparent communication of seasonality-related research across different communities.