Articles | Volume 30, issue 2
https://doi.org/10.5194/npg-30-167-2023
https://doi.org/10.5194/npg-30-167-2023
Research article
 | 
15 Jun 2023
Research article |  | 15 Jun 2023

Exploring meteorological droughts' spatial patterns across Europe through complex network theory

Domenico Giaquinto, Warner Marzocchi, and Jürgen Kurths

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Cited articles

Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B., and Kurths, J.: Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach, Nonlin. Processes Geophys., 24, 599–611, https://doi.org/10.5194/npg-24-599-2017, 2017. a
Bastos, A., Fu, Z., Ciais, P., Friedlingstein, P., Sitch, S., Pongratz, J.,Weber, U., Reichstein, M., Anthoni, P., Arneth, A., Haverd, V., Jain, A., Joetzjer, E., Knauer, J., Lienert, S., Loughran, T., McGuire, P. C., Obermeier, W., Padrón, R. S., Shi, H., Tian, H., Viovy N., and Zaehle, S.: Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018, Philos. T. R. Soc.. B, 375, 20190507, https://doi.org/10.1098/rstb.2019.0507, 2020. a
Beillouin, D., Schauberger, B., Bastos, A., Ciais, P., and Makowski, D.: Impact of extreme weather conditions on European crop production in 2018, Philos. T. R. Soc.. B, 375, 20190510, https://doi.org/10.1098/rstb.2019.0510, 2020. a
Benito, G., Machado, M. J., and Pérez-González, A.: Climate change and flood sensitivity in Spain, Geological Society, London, Special Publications, 115, 85–98, 1996. a
Bevacqua, A. G., Chaffe, P. L., Chagas, V. B., and AghaKouchak, A.: Spatial and temporal patterns of propagation from meteorological to hydrological droughts in Brazil, J. Hydrol., 603, 126902, https://doi.org/10.1016/j.jhydrol.2021.126902, 2021. a
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Short summary
Despite being among the most severe climate extremes, it is still challenging to assess droughts’ features for specific regions. In this paper we study meteorological droughts in Europe using concepts derived from climate network theory. By exploring the synchronization in droughts occurrences across the continent we unveil regional clusters which are individually examined to identify droughts’ geographical propagation and source–sink systems, which could potentially support droughts’ forecast.