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Author: Arneth, Almut × Subject: size distribution ×

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    Detecting impacts of extreme events with ecological in situ monitoring networks
    (München : European Geopyhsical Union, 2017) Mahecha, Miguel D.; Gans, Fabian; Sippel, Sebastian; Donges, Jonathan F.; Kaminski, Thomas; Metzger, Stefan; Migliavacca, Mirco; Papale, Dario; Rammig, Anja; Zscheischler, Jakob; Arneth, Almut
    Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR), identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log–log space. For instance, networks with  ≈  100 randomly placed sites in Europe yield a  ≥  90 % chance of detecting the eight largest (typically very large) extreme events; but only a  ≥  50 % chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON) reliably detect the largest extremes, but that the extreme event detection rates are not higher than would be achieved by randomly designed networks. Spatio-temporal expansions of ecological in situ monitoring networks should carefully consider the size distribution characteristics of extreme events if the aim is also to monitor the impacts of such events in the terrestrial biosphere.
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    Aerosol particle formation events and analysis of high growth rates observed above a subarctic wetland-forest mosaic
    (Milton Park : Taylor & Francis, 2017) Svenningsson, Birgitta; Arneth, Almut; Hayward, Sean; Holst, Thomas; Massling, Andreas; Swietlicki, Erik; Hirsikko, Anne; Junninen, Heikki; Riipinen, Ilona; Vana, Marko; Dal Maso, Miikka; Hussein, Tareq; Kulmala, Markku
    An analysis of particle formation (PF) events over a subarctic mire in northern Swedenwas performed, based on number– size distributions of atmospheric aerosol particles (10–500 nm in diameter) and ions (0.4–40 nm in Tammet diameter). We present classification statistics for PF events from measurements covering the period July 2005–September 2006, with a break over the winter period. The PF event frequency peaked during the summer months, in contrast to other Scandinavian sites where the frequency is highest during spring and autumn. Our analysis includes calculated growth rates and estimates of concentrations and production rates of condensing vapour, deduced from the growth rates and condensational sink calculations, using AIS and SMPS data. Particle formation events with high growth rates (up to 50 nm h-1) occurred repeatedly. In these cases, the newly formed nucleation mode particles were often only present for periods of a few hours. On several occasions, repeated particle formation events were observed within 1 d, with differences in onset time of a few hours. These high growth rates were only observed when the condensation sink was higher than 0.001 s-1.