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Subject: spatiotemporal analysis ×

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Now showing 1 - 10 of 26
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    High spatial and temporal resolution cell manipulation techniques in microchannels
    (Cambridge : Royal Society of Chemistry, 2016) Novo, Pedro; Dell’Aica, Margherita; Janasek, Dirk; Zahedi, René P.
    The advent of microfluidics has enabled thorough control of cell manipulation experiments in so called lab on chips. Lab on chips foster the integration of actuation and detection systems, and require minute sample and reagent amounts. Typically employed microfluidic structures have similar dimensions as cells, enabling precise spatial and temporal control of individual cells and their local environments. Several strategies for high spatio-temporal control of cells in microfluidics have been reported in recent years, namely methods relying on careful design of the microfluidic structures (e.g. pinched flow), by integration of actuators (e.g. electrodes or magnets for dielectro-, acousto- and magneto-phoresis), or integrations thereof. This review presents the recent developments of cell experiments in microfluidics divided into two parts: an introduction to spatial control of cells in microchannels followed by special emphasis in the high temporal control of cell-stimulus reaction and quenching. In the end, the present state of the art is discussed in line with future perspectives and challenges for translating these devices into routine applications.
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    Regional effects of atmospheric aerosols on temperature: An evaluation of an ensemble of online coupled models
    (Katlenburg-Lindau : EGU, 2017) Baró, Rocío; Palacios-Peña, Laura; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro
    The climate effect of atmospheric aerosols is associated with their influence on the radiative budget of the Earth due to the direct aerosol-radiation interactions (ARIs) and indirect effects, resulting from aerosol-cloud-radiation interactions (ACIs). Online coupled meteorology-chemistry models permit the description of these effects on the basis of simulated atmospheric aerosol concentrations, although there is still some uncertainty associated with the use of these models. Thus, the objective of this work is to assess whether the inclusion of atmospheric aerosol radiative feedbacks of an ensemble of online coupled models improves the simulation results for maximum, mean and minimum temperature at 2m over Europe. The evaluated models outputs originate from EuMetChem COST Action ES1004 simulations for Europe, differing in the inclusion (or omission) of ARI and ACI in the various models. The cases studies cover two important atmospheric aerosol episodes over Europe in the year 2010: (i) a heat wave event and a forest fire episode (July-August 2010) and (ii) a more humid episode including a Saharan desert dust outbreak in October 2010. The simulation results are evaluated against observational data from the E-OBS gridded database. The results indicate that, although there is only a slight improvement in the bias of the simulation results when including the radiative feedbacks, the spatiotemporal variability and correlation coefficients are improved for the cases under study when atmospheric aerosol radiative effects are included.
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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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    Extreme events in gross primary production: A characterization across continents
    (München : European Geopyhsical Union, 2014) Zscheischler, J.; Reichstein, M.; Harmeling, S.; Rammig, A.; Tomelleri, E.; Mahecha, M.D.
    Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.
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    Enhancing the spatiotemporal features of polar mesosphere summer echoes using coherent MIMO and radar imaging at MAARSY
    (Göttingen : Copernicus GmbH, 2019) Urco, J.M.; Chau, J.L.; Weber, T.; Latteck, R.
    Polar mesospheric summer echoes (PMSEs) are very strong radar echoes caused by the presence of ice particles, turbulence, and free electrons in the mesosphere over polar regions. For more than three decades, PMSEs have been used as natural tracers of the complicated atmospheric dynamics of this region. Neutral winds and turbulence parameters have been obtained assuming PMSE horizontal homogeneity on scales of tens of kilometers. Recent radar imaging studies have shown that PMSEs are not homogeneous on these scales and instead they are composed of kilometer-scale structures. In this paper, we present a technique that allows PMSE observations with unprecedented angular resolution (∼0.6). The technique combines the concept of coherent MIMO (Multiple Input Multiple Output) and two high-resolution imaging techniques, i.e., Capon and maximum entropy (MaxEnt). The resulting resolution is evaluated by imaging specular meteor echoes. The gain in angular resolution compared to previous approaches using SIMO (Single Input Multiple Output) and Capon is at least a factor of 2; i.e., at 85 km, we obtain a horizontal resolution of ∼900 m. The advantage of the new technique is evaluated with two events of 3-D PMSE structures showing: (1) horizontal wavelengths of 8-10 km and periods of 4-7 min, drifting with the background wind, and (2) horizontal wavelengths of 12-16 km and periods of 15-20 min, not drifting with the background wind. Besides the advantages of the implemented technique, we discuss its current challenges, like the use of reduced power aperture and processing time, as well as the future opportunities for improving the understanding of the complex small-scale atmospheric dynamics behind PMSEs. © 2019 Author(s).
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    Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies
    (Katlenburg-Lindau : EGU, 2017) Mu, Qing; Lammel, Gerhard; Gencarelli, Christian N.; Hedgecock, Ian M.; Chen, Ying; Přibylová, Petra; Teich, Monique; Zhang, Yuxuan; Zheng, Guangjie; van Pinxteren, Dominik; Zhang, Qiang; Herrmann, Hartmut; Shiraiwa, Manabu; Spichtinger, Peter; Su, Hang; Pöschl, Ulrich; Cheng, Yafang
    Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.
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    Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers
    (Katlenburg-Lindau : EGU, 2017) Madhavan, Bomidi Lakshmi; Deneke, Hartwig; Witthuhn, Jonas; Macke, Andreas
    The time series of global radiation observed by a dense network of 99 autonomous pyranometers during the HOPE campaign around Jülich, Germany, are investigated with a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet. For different sky conditions, typical wavelet power spectra are calculated to quantify the timescale dependence of variability in global transmittance. Distinctly higher variability is observed at all frequencies in the power spectra of global transmittance under broken-cloud conditions compared to clear, cirrus, or overcast skies. The spatial autocorrelation function including its frequency dependence is determined to quantify the degree of similarity of two time series measurements as a function of their spatial separation. Distances ranging from 100-m to 10-km are considered, and a rapid decrease of the autocorrelation function is found with increasing frequency and distance. For frequencies above 1-3-ming-1 and points separated by more than 1-km, variations in transmittance become completely uncorrelated. A method is introduced to estimate the deviation between a point measurement and a spatially averaged value for a surrounding domain, which takes into account domain size and averaging period, and is used to explore the representativeness of a single pyranometer observation for its surrounding region. Two distinct mechanisms are identified, which limit the representativeness; on the one hand, spatial averaging reduces variability and thus modifies the shape of the power spectrum. On the other hand, the correlation of variations of the spatially averaged field and a point measurement decreases rapidly with increasing temporal frequency. For a grid box of 10-km-×-10-km and averaging periods of 1.5-3-h, the deviation of global transmittance between a point measurement and an area-averaged value depends on the prevailing sky conditions: 2.8 (clear), 1.8 (cirrus), 1.5 (overcast), and 4.2-% (broken clouds). The solar global radiation observed at a single station is found to deviate from the spatial average by as much as 14-23 (clear), 8-26 (cirrus), 4-23 (overcast), and 31-79-Wg-mg-2 (broken clouds) from domain averages ranging from 1-km-×-1-km to 10-km-×-10-km in area.
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    Climate of the last millennium: Ensemble consistency of simulations and reconstructions
    (Göttingen : Copernicus, 2013) Bothe, O.; Jungclaus, J.H.; Zanchettin, D.; Zorita, E.
    Are simulations and reconstructions of past climate and its variability consistent with each other? We assess the consistency of simulations and reconstructions for the climate of the last millennium under the paradigm of a statistically indistinguishable ensemble. In this type of analysis, the null hypothesis is that reconstructions and simulations are statistically indistinguishable and, therefore, are exchangeable with each other. Ensemble consistency is assessed for Northern Hemisphere mean temperature, Central European mean temperature and for global temperature fields. Reconstructions available for these regions serve as verification data for a set of simulations of the climate of the last millennium performed at the Max Planck Institute for Meteorology. Consistency is generally limited to some sub-domains and some sub-periods. Only the ensemble simulated and reconstructed annual Central European mean temperatures for the second half of the last millennium demonstrates unambiguous consistency. Furthermore, we cannot exclude consistency of an ensemble of reconstructions of Northern Hemisphere temperature with the simulation ensemble mean. If we treat simulations and reconstructions as equitable hypotheses about past climate variability, the found general lack of their consistency weakens our confidence in inferences about past climate evolutions on the considered spatial and temporal scales. That is, our available estimates of past climate evolutions are on an equal footing but, as shown here, inconsistent with each other.
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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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    From biota to chemistry and climate: Towards a comprehensive description of trace gas exchange between the biosphere and atmosphere
    (München : European Geopyhsical Union, 2010) Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I.C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.
    Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.