@article{BaumbachSiegmundMittermeieretal.2017, author = {Baumbach, Lukas and Siegmund, Jonatan F. and Mittermeier, Magdalena and Donner, Reik Volker}, title = {Impacts of temperature extremes on European vegetation during the growing season}, series = {Biogeosciences}, volume = {14}, journal = {Biogeosciences}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1726-4170}, doi = {10.5194/bg-14-4891-2017}, pages = {4891 -- 4903}, year = {2017}, abstract = {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.}, language = {en} } @article{DongesSchleussnerSiegmundetal.2016, author = {Donges, Jonathan Friedemann and Schleussner, C. -F. and Siegmund, Jonatan F. and Donner, Reik Volker}, title = {Event coincidence analysis for quantifying statistical interrelationships between event time series}, series = {European physical journal special topics}, volume = {225}, journal = {European physical journal special topics}, publisher = {Springer}, address = {Heidelberg}, issn = {1951-6355}, doi = {10.1140/epjst/e2015-50233-y}, pages = {471 -- 487}, year = {2016}, abstract = {Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.}, language = {en} } @article{SiegmundWiedermannDongesetal.2016, author = {Siegmund, Jonatan F. and Wiedermann, Marc and Donges, Jonathan Friedemann and Donner, Reik Volker}, title = {Impact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species}, series = {Biogeosciences}, volume = {13}, journal = {Biogeosciences}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1726-4170}, doi = {10.5194/bg-13-5541-2016}, pages = {5541 -- 5555}, year = {2016}, abstract = {Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering.}, language = {en} } @article{SiegmundSandersHeinrichetal.2016, author = {Siegmund, Jonatan F. and Sanders, Tanja G. M. and Heinrich, Ingo and van der Maaten, Ernst and Simard, Sonia and Helle, Gerhard and Donner, Reik Volker}, title = {Meteorological Drivers of Extremes in Daily Stem Radius Variations of Beech, Oak, and Pine in Northeastern Germany: An Event Coincidence Analysis}, series = {Frontiers in plant science}, volume = {7}, journal = {Frontiers in plant science}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2016.00733}, pages = {4701 -- 4712}, year = {2016}, abstract = {Observed recent and expected future increases in frequency and intensity of climatic extremes in central Europe may pose critical challenges for domestic tree species. Continuous dendrometer recordings provide a valuable source of information on tree stem radius variations, offering the possibility to study a tree's response to environmental influences at a high temporal resolution. In this study, we analyze stem radius variations (SRV) of three domestic tree species (beech, oak, and pine) from 2012 to 2014. We use the novel statistical approach of event coincidence analysis (ECA) to investigate the simultaneous occurrence of extreme daily weather conditions and extreme SRVs, where extremes are defined with respect to the common values at a given phase of the annual growth period. Besides defining extreme events based on individual meteorological variables, we additionally introduce conditional and joint ECA as new multivariate extensions of the original methodology and apply them for testing 105 different combinations of variables regarding their impact on SRV extremes. Our results reveal a strong susceptibility of all three species to the extremes of several meteorological variables. Yet, the inter-species differences regarding their response to the meteorological extremes are comparatively low. The obtained results provide a thorough extension of previous correlation-based studies by emphasizing on the timings of climatic extremes only. We suggest that the employed methodological approach should be further promoted in forest research regarding the investigation of tree responses to changing environmental conditions.}, language = {en} }