87 – STATMOS/NCAR Statistics in the Atmospheric Sciences
Globolakes: Functional Clustering and Global Scale Coherence of Lake Water Quality
Ruth Haggarty
University of Glasgow
Claire Miller
University of Glasgow
Marian Scott
University of Glasgow
Lakes are considered as sensitive indicators of environmental change which are impacted by both natural and anthropogenic drivers. The potential impact of climate change on freshwater resources is critical, and improved understanding of the observed changes is key to ensure better management of aquatic resources. While previous studies have often focussed on individual lakes, identifying synchronous temporal patterns observed across multiple lakes on a larger scale may indicate the existence of global common drivers and pressures. The GloboLakes project includes statistical analysis of remotely sensed data for lakes across the world in order to investigate how lake water quality responds to environmental change at a global scale. The aim of this paper is to investigate different clustering approaches for functional data applied to Lake Surface Water Temperature data. The clustering will be used to explore temporal coherence of multiple time series, with a view to establishing ecologically valid groups of lakes which are similar in terms of observed trends and seasonal patterns.