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    Impacts of temperature extremes on European vegetation during the growing season
    (München : European Geopyhsical Union, 2017) Baumbach, Lukas; Siegmund, Jonatan F.; Mittermeier, Magdalena; Donner, Reik V.
    Temperature is a key factor controlling plant growth and vitality in the temperate climates of the mid-latitudes like in vast parts of the European continent. Beyond the effect of average conditions, the timings and magnitudes of temperature extremes play a particularly crucial role, which needs to be better understood in the context of projected future rises in the frequency and/or intensity of such events. In this work, we employ event coincidence analysis (ECA) to quantify the likelihood of simultaneous occurrences of extremes in daytime land surface temperature anomalies (LSTAD) and the normalized difference vegetation index (NDVI). We perform this analysis for entire Europe based upon remote sensing data, differentiating between three periods corresponding to different stages of plant development during the growing season. In addition, we analyze the typical elevation and land cover type of the regions showing significantly large event coincidences rates to identify the most severely affected vegetation types. Our results reveal distinct spatio-temporal impact patterns in terms of extraordinarily large co-occurrence rates between several combinations of temperature and NDVI extremes. Croplands are among the most frequently affected land cover types, while elevation is found to have only a minor effect on the spatial distribution of corresponding extreme weather impacts. These findings provide important insights into the vulnerability of European terrestrial ecosystems to extreme temperature events and demonstrate how event-based statistics like ECA can provide a valuable perspective on environmental nexuses.
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    A climate network perspective on the intertropical convergence zone
    (Göttingen : Copernicus Publ., 2021) Wolf, Frederik; Voigt, Aiko; Donner, Reik V.
    The intertropical convergence zone (ITCZ) is an important component of the tropical rain belt. Climate models continue to struggle to adequately represent the ITCZ and differ substantially in its simulated response to climate change. Here we employ complex network approaches, which extract spatiotemporal variability patterns from climate data, to better understand differences in the dynamics of the ITCZ in state-of-the-art global circulation models (GCMs). For this purpose, we study simulations with 14 GCMs in an idealized slab-ocean aquaplanet setup from TRACMIP – the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project. We construct network representations based on the spatial correlation patterns of monthly surface temperature anomalies and study the zonal-mean patterns of different topological and spatial network characteristics. Specifically, we cluster the GCMs by means of the distributions of their zonal network measures utilizing hierarchical clustering. We find that in the control simulation, the distributions of the zonal network measures are able to pick up model differences in the tropical sea surface temperature (SST) contrast, the ITCZ position, and the strength of the Southern Hemisphere Hadley cell. Although we do not find evidence for consistent modifications in the network structure tracing the response of the ITCZ to global warming in the considered model ensemble, our analysis demonstrates that coherent variations of the global SST field are linked to ITCZ dynamics. This suggests that climate networks can provide a new perspective on ITCZ dynamics and model differences therein.