Features of the Earth's seasonal hydroclimate: Characterizations and comparisons across the Koppen-Geiger climates and across continents

Detailed feature investigations and comparisons across climates, continents and time series types can progress our understanding and modelling ability of the Earth's hydroclimate and its dynamics. As a step towards these important directions, we here propose and extensively apply a multifaceted and engineering-friendly methodological framework for the thorough characterization of seasonal hydroclimatic dependence, variability and change at the global scale. We apply this framework using over 13 000 quarterly temperature, precipitation and river flow time series. In these time series, the seasonal hydroclimatic behaviour is represented by 3-month means of earth-observed variables. In our analyses, we also adopt the well-established Koppen-Geiger climate classification system and define continental-scale regions with large or medium density of observational stations. In this context, we provide in parallel seasonal hydroclimatic feature summaries and comparisons in terms of autocorrelation, seasonality, temporal variation, entropy, long-range dependence and trends. We find notable differences to characterize the magnitudes of most of these features across the various Koppen-Geiger climate classes, as well as between several continental-scale geographical regions. We, therefore, deem that the consideration of the comparative summaries could be more beneficial in water resources engineering contexts than the also provided global summaries. Lastly, we apply explainable machine learning to compare the investigated features with respect to how informative they are in explaining and predicting either the main Koppen-Geiger climate or the continental-scale region, with the entropy, long-range dependence and trend features being (roughly) found to be less informative than the remaining ones at the seasonal time scale.

Hydroclimatic time series features at multiple time scales

A comprehensive understanding of the behaviours of the various geophysical processes requires, among others, detailed investigations across temporal scales. In this work, we propose a new time series feature compilation for advancing and enriching such investigations in a hydroclimatic context. This specific compilation can facilitate largely interpretable feature investigations and comparisons in terms of temporal dependence, temporal variation, "forecastability", lumpiness, stability, nonlinearity (and linearity), trends, spikiness, curvature and seasonality. Detailed quantifications and multifaceted characterizations are herein obtained by computing the values of the proposed feature compilation across nine temporal resolutions (i.e., the 1-day, 2-day, 3-day, 7-day, 0.5-month, 1-month, 2-month, 3-month and 6-month ones) and three hydroclimatic time series types (i.e., temperature, precipitation and streamflow) for 34-year-long time series records originating from 511 geographical locations across the continental United States. Based on the acquired information and knowledge, similarities and differences between the examined time series types with respect to the evolution patterns characterizing their feature values with increasing (or decreasing) temporal resolution are identified. To our view, the similarities in these patterns are rather surprising. We also find that the spatial patterns emerging from feature-based time series clustering are largely analogous across temporal scales, and compare the features with respect to their usefulness in clustering the time series at the various temporal resolutions. For most of the features, this usefulness can vary to a notable degree across temporal resolutions and time series types, thereby pointing out the need for conducting multifaceted time series characterizations for the study of hydroclimatic similarity.