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

• URL: http://arxiv.org/abs/2204.06544v1
• Date: Wed, 13 Apr 2022 17:42:57 GMT
• Title: Features of the Earth's seasonal hydroclimate: Characterizations and comparisons across the Koppen-Geiger climates and across continents
• Authors: Georgia Papacharalampous, Hristos Tyralis, Yannis Markonis, Petr Maca, Martin Hanel
• Abstract summary: We 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 provide in parallel seasonal hydroclimatic feature summaries and comparisons in terms of autocorrelation, seasonality, temporal variation, entropy, long-range dependence and trends.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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