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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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    The spectral aerosol extinction monitoring system (SÇMS): Setup, observational products, and comparisons
    (München : European Geopyhsical Union, 2014) Skupin, A.; Ansmann, A.; Engelmann, R.; Baars, H.; Müller, T.
    The Spectral Aerosol Extinction Monitoring System (SÇMS) is presented that allows us to continuously measure the spectral extinction coefficient of atmospheric aerosol particles along an approximately 2.7 km long optical path at 30–50 m height above ground in Leipzig (51.3° N, 12.4° E), Germany. The fully automated instrument measures the ambient aerosol extinction coefficients from 300 to 1000 nm. The main goal of (SÇMS) observations are long-term studies of the relationship between particle extinction and relative humidity from below 40% to almost 100%. The setup is presented and observations (a case study and statistical results for 2009) are discussed in terms of time series of 550 nm particle optical depth, Ångström exponent, and particle size distribution retrieved from the spectrally resolved extinction. The SǼMS measurements are compared with simultaneously performed EARLINET (European Aerosol Research Lidar Network) lidar, AERONET (Aerosol Robotic Network) sun photometer, and in situ aerosol observations of particle size distribution and related extinction coefficients on the roof of our institute. Consistency between the different measurements is found, which corroborates the quality of the SǼMS observations. Statistical results of a period of 1 yr (2009) show mode extinction values of 0.09 km−1 (SÇMS), 0.075 km−1 (AERONET), and 0.03 km−1 (in situ). Ångström exponents for this period are 0.19 (390–880 nm,(SÇMS) and 1.55 (440–870 nm, AERONET).
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    EARLINET: Potential operationality of a research network
    (München : European Geopyhsical Union, 2015) Sicard, M.; D'Amico, G.; Comerón, A.; Mona, L.; Alados-Arboledas, L.; Amodeo, A.; Baars, H.; Baldasano, J.M.; Belegante, L.; Binietoglou, I.; Bravo-Aranda, J.A.; Fernández, A.J.; Fréville, P.; García-Vizcaíno, D.; Giunta, A.; Granados-Muñoz, M.J.; Guerrero-Rascado, J.L.; Hadjimitsis, D.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R.E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.
    In the framework of ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated in the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time, the single calculus chain (SCC) – the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products – was used. All stations sent in real-time measurements of a 1 h duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC, while the optical processing was performed in near-real time after the exercise ended. 98 and 79 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on the lidar data. The paper draws present and future SCC users' attention to the most critical parameters of the SCC product configuration and their possible optimal value but also to the limitations inherent to the raw data. The continuous use of SCC direct and derived products in heterogeneous conditions is used to demonstrate two potential applications of EARLINET infrastructure: the monitoring of a Saharan dust intrusion event and the evaluation of two dust transport models. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modeling, climate research and calibration/validation activities of spaceborne observations.
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    The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds - Case studies
    (Katlenburg-Lindau : EGU, 2020) Jimenez, Cristofer; Ansmann, Albert; Engelmann, Ronny; Donovan, David; Malinka, Aleksey; Seifert, Patric; Wiesen, Robert; Radenz, Martin; Yin, Zhenping; Bühl, Johannes; Schmidt, Jörg; Barja, Boris; Wandinger, Ulla
    In a companion article (Jimenez et al., 2020), we introduced a new lidar method to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration Nd) at a height of 50-100m above the cloud base together with aerosol information (aerosol extinction coefficients, cloud condensation nuclei concentration NCCN) below the cloud layer so that detailed studies of the influence of given aerosol conditions on the evolution of liquid-water cloud layers with high temporal resolution solely based on lidar observations have become possible now. The novel cloud retrieval technique makes use of lidar observations of the volume linear depolarization ratio at two different receiver field of views (FOVs). In this article, Part 2, the new dual-FOV polarization lidar technique is applied to cloud measurements in pristine marine conditions at Punta Arenas in southern Chile. A multiwavelength polarization Raman lidar, upgraded by integrating a second polarization-sensitive channel to permit depolarization ratio observations at two FOVs, was used for these measurements at the southernmost tip of South America. Two case studies are presented to demonstrate the potential of the new lidar technique. Successful aerosol-cloud-interaction (ACI) studies based on measurements with the upgraded aerosol-cloud lidar in combination with a Doppler lidar of the vertical wind component could be carried out with 1 min temporal resolution at these pristine conditions. In a stratocumulus layer at the top of the convective boundary layer, we found values of Nd and NCCN (for 0.2% water supersaturation) ranging from 15-100 and 75-200 cm-3, respectively, during updraft periods. The studies of the aerosol impact on cloud properties yielded ACI values close to 1. The impact of aerosol water uptake on the ACI studies was analyzed with the result that the highest ACI values were obtained when considering aerosol proxies (light-extinction coefficient par or NCCN) measured at heights about 500m below the cloud base (and thus for dry aerosol conditions). © 2020 BMJ Publishing Group. All rights reserved.
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    Monitoring der methanbildenden Mikroflora in Praxis-Biogasanlagen im ländlichen Raum : Analyse des Ist-Zustandes und Entwicklung eines quantitativen Nachweissystems
    (Hannover : Technische Informationsbibliothek, 2009) Klocke, Michael; Nettmann, Edith; Bergmann, Ingo
    Die Produktion von Biogas aus landwirtschaftlichen Primärprodukten oder Reststoffen stellt einen wesentlichen Beitrag zur Reduktion des Co2-Ausstoßes sowie zur Entwicklung einer nachhaltigen Landbewirtschaftung dar. Im Rahmen dieses Projektes soll daher die Artenzusammensetzung der methanogenen Mikroflora in ausgewählten Praxis-Biogasanlagen anhand ihrer 16S rDNA analysisert werden.
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    Real-Time Monitoring of Blood Parameters in the Intensive Care Unit: State-of-the-Art and Perspectives
    (Basel : MDPI, 2022) Bockholt, Rebecca; Paschke, Shaleen; Heubner, Lars; Ibarlucea, Bergoi; Laupp, Alexander; Janićijević, Željko; Klinghammer, Stephanie; Balakin, Sascha; Maitz, Manfred F.; Werner, Carsten; Cuniberti, Gianaurelio; Baraban, Larysa; Spieth, Peter Markus
    The number of patients in intensive care units has increased over the past years. Critically ill patients are treated with a real time support of the instruments that offer monitoring of relevant blood parameters. These parameters include blood gases, lactate, and glucose, as well as pH and tem-perature. Considering the COVID-19 pandemic, continuous management of dynamic deteriorating parameters in patients is more relevant than ever before. This narrative review aims to summarize the currently available literature regarding real-time monitoring of blood parameters in intensive care. Both, invasive and non-invasive methods are described in detail and discussed in terms of general advantages and disadvantages particularly in context of their use in different medical fields but especially in critical care. The objective is to explicate both, well-known and frequently used as well as relatively unknown devices. Furtehrmore, potential future direction in research and development of realtime sensor systems are discussed. Therefore, the discussion section provides a brief description of current developments in biosensing with special emphasis on their technical implementation. In connection with these developments, the authors focus on different electrochemical approaches to invasive and non-invasive measurements in vivo.
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    Early Detection of Stripe Rust in Winter Wheat Using Deep Residual Neural Networks
    (Lausanne : Frontiers Media, 2021) Schirrmann, Michael; Landwehr, Niels; Giebel, Antje; Garz, Andreas; Dammer, Karl-Heinz
    Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 × 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks.
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    Ground-penetrating radar insight into a coastal aquifer: the freshwater lens of Borkum Island
    (Munich : EGU, 2013) Igel, J.; Günther, T.; Kuntzer, M.
    Freshwater lenses, as important resource for drinking water, are sensitive to climate changes and sea level rise. To simulate this impact on the groundwater systems, hydraulic subsurface models have to be designed. Geophysical techniques can provide information for generating realistic models. The aim of our work is to show how ground-penetrating radar (GPR) investigations can contribute to such hydrological simulations. In the pilot area, Borkum island, GPR was used to map the shape of the groundwater table (GWT) and to characterise the aquifer. In total, 20 km of constant offset (CO) profiles were measured with centre frequencies of 80 and 200 MHz. Wave velocities were determined by common midpoint (CMP) measurements and vertical radar profiling (VRP) in a monitoring well. The 80 MHz CO data show a clear reflection at the groundwater table, whereas the reflection is weaker for the 200 MHz data. After correcting the GPR water tables for the capillary rise, they are in good accordance with the pressure heads of the observation wells in the area. In the centre of the island, the groundwater table is found up to 3.5 m above sea level, however it is lower towards the coastline and marshland. Some local depressions are observed in the region of dune valleys and around pumping stations of the local water supplier. GPR also reveals details within the sediments and highly-permeable aeolian sands can be distinguished from less-permeable marine sediments. Further, a silt loam layer below the water table could be mapped on a large area. The reflection characteristics indicates scattered erosion channels in this layer that cause it to be an aquitard with some leakage. GPR provides a high resolution map of the groundwater table and insight into the stratigraphy of the sediments and their hydraulic properties. This is valuable complementary information to the observation of sparsely distributed monitoring wells as input to hydraulic simulation.
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    Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography
    (Munich : EGU, 2013) Beff, L.; Günther, T.; Vandoorne, B.; Couvreur, V.; Javaux, M.
    A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that Electrical Resistivity Tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). This study was conducted (i) to check and validate how ERT is able to monitor SWC distribution in a maize field during the late growing season; and (ii) to investigate how maize plants and rainfall affect the dynamics of SWC distribution. Time Domain Reflectometry (TDR) measurements were used to validate ERT-inverted SWC values. Evolution of water mass balance was also calculated to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. It is observed that ERT was able to give the same average SWC as TDR (R2 = 0.98). In addition, ERT gives better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows for the discrimination of SWC heterogeneities. The SWC distribution showed that alternation of maize rows and inter-rows was the main influencing factor of the SWC distribution. The drying patterns were linked to the root profiles, with drier zones under the maize rows. During short periods, with negligible rainfall, the SWC decrease took place mainly in the two upper soil horizons and in the inter-row area. In contrast, rainfall increased the SWC mostly under the maize rows and in the upper soil layer. Nevertheless, the total amount of rainfall during the growing season was not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, there was hardly any SWC redistribution from maize rows to inter-rows. Yet, lateral redistribution from inter-rows to maize rows induced by potential gradient generates SWC decrease in the inter-row area and in the deeper soil horizons.
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    Profiling of aerosol microphysical properties at several EARLINET/AERONET sites during the July 2012 ChArMEx/EMEP campaign
    (München : European Geopyhsical Union, 2016) Granados-Muñoz, María José; Navas-Guzmán, Francisco; Guerrero-Rascado, Juan Luis; Bravo-Aranda, Juan Antonio; Pereira, Sergio Nepomuceno; Basart, Sara; Baldasano, José María; Belegante, Livio; Chaikovsky, Anatoli; Comerón, Adolfo; D'Amico, Giuseppe; Dubovik, Oleg; Ilic, Luka; Kokkalis, Panos; Muñoz-Porcar, Constantino; Nickovic, Slobodan; Nicolae, Doina; Facchini, Maria Cristina; Olmo, Francisco José; Papayannis, Alexander; Pappalardo, Gelsomina; Rodríguez, Alejandro; Schepanski, Kerstin; Sicard, Michaël; Vukovic, Ana; Wandinger, Ulla; Dulac, François; Alados-Arboledas, Lucas
    The simultaneous analysis of aerosol microphysical properties profiles at different European stations is made in the framework of the ChArMEx/EMEP 2012 field campaign (9–11 July 2012). During and in support of this campaign, five lidar ground-based stations (Athens, Barcelona, Bucharest, Évora, and Granada) performed 72 h of continuous lidar measurements and collocated and coincident sun-photometer measurements. Therefore it was possible to retrieve volume concentration profiles with the Lidar Radiometer Inversion Code (LIRIC). Results indicated the presence of a mineral dust plume affecting the western Mediterranean region (mainly the Granada station), whereas a different aerosol plume was observed over the Balkans area. LIRIC profiles showed a predominance of coarse spheroid particles above Granada, as expected for mineral dust, and an aerosol plume composed mainly of fine and coarse spherical particles above Athens and Bucharest. Due to the exceptional characteristics of the ChArMEx database, the analysis of the microphysical properties profiles' temporal evolution was also possible. An in-depth analysis was performed mainly at the Granada station because of the availability of continuous lidar measurements and frequent AERONET inversion retrievals. The analysis at Granada was of special interest since the station was affected by mineral dust during the complete analyzed period. LIRIC was found to be a very useful tool for performing continuous monitoring of mineral dust, allowing for the analysis of the dynamics of the dust event in the vertical and temporal coordinates. Results obtained here illustrate the importance of having collocated and simultaneous advanced lidar and sun-photometer measurements in order to characterize the aerosol microphysical properties in both the vertical and temporal coordinates at a regional scale. In addition, this study revealed that the use of the depolarization information as input in LIRIC in the stations of Bucharest, Évora, and Granada was crucial for the characterization of the aerosol types and their distribution in the vertical column, whereas in stations lacking depolarization lidar channels, ancillary information was needed. Results obtained were also used for the validation of different mineral dust models. In general, the models better forecast the vertical distribution of the mineral dust than the column-integrated mass concentration, which was underestimated in most of the cases.