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Philipp A. Lange and Heinrich Hühnerfuss

Abstract

Surface tension gradients have been measured for three different monolayers (oleyl alcohol, palmitic acid methyl ester and cetyl trimethyl ammonium bromide) spread on a wavy water surface (waves with 1-Hz frequency; 2 cm wave height). The wave-induced surface tension gradients were determined indirectly using 1) a wave-follower mounted surface-potential ionization probe and 2) a pulsating spreading oil patch. The films can sustain unexpectedly large surface tension variations of the order 12–14 (×10−3) N m−1 and were found to experience a relaxation, i.e., a significant change of surface potential and surface tension variation with time (order of 1500 s) and with position on the wave (phase shift). The relaxation and phase shift are attributed to a reordering of the film molecules and the subsequent modification of the mutual interaction between the film molecules and the water molecules of the underlying water layer.

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D. R. Fereday, J. R. Knight, A. A. Scaife, C. K. Folland, and A. Philipp

Abstract

Observed atmospheric circulation over the North Atlantic–European (NAE) region is examined using cluster analysis. A clustering algorithm incorporating a “simulated annealing” methodology is employed to improve on solutions found by the conventional k-means technique. Clustering is applied to daily mean sea level pressure (MSLP) fields to derive a set of circulation types for six 2-month seasons. A measure of the quality of this clustering is defined to reflect the average similarity of the fields in a cluster to each other. It is shown that a range of classifications can be produced for which this measure is almost identical but which partition the days quite differently. This lack of a unique set of circulation types suggests that distinct weather regimes in NAE circulation do not exist or are very weak. It is also shown that the stability of the clustering solution to removal of data is not maximized by a suitable choice of the number of clusters. Indeed, there does not appear to be any robust way of choosing an optimum number of circulation types. Despite the apparent lack of preferred circulation types, cluster analysis can usefully be applied to generate a set of patterns that fully characterize the different circulation types appearing in each season. These patterns can then be used to analyze NAE climate variability. Ten clusters per season are chosen to ensure that a range of distinct circulation types that span the variability is produced. Using this classification, the effect of forcing of NAE circulation by tropical Pacific sea surface temperature (SST) anomalies is analyzed. This shows a significant influence of SST in this region on certain circulation types in almost all seasons. A tendency for a negative correlation between El Niño and an anomaly pattern resembling the positive winter North Atlantic Oscillation (NAO) emerges in a number of seasons. A notable exception is November–December, which shows the opposite relationship, with positive NAO-like patterns correlated with El Niño.

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A. Philipp, P. M. Della-Marta, J. Jacobeit, D. R. Fereday, P. D. Jones, A. Moberg, and H. Wanner

Abstract

Reconstructed daily mean sea level pressure patterns of the North Atlantic–European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum and more stable. The differences between conventional cluster analysis and the SANDRA scheme are significant for subsequent analyses of single clusters—in particular, for trend analysis. Conventional indices used to determine the appropriate number of clusters failed to provide clear guidance, indicating that no distinct separation between clusters of circulation types exists in the dataset. Therefore, the number of clusters is determined by an external indicator, the so-called dominance criteria for t-mode principal component analysis. Nevertheless, the resulting partitions are stable for certain numbers of clusters and provide meaningful and reproducible clusters. The resulting types of pressure patterns reveal pronounced long-term variability and various significant trends of the time series of seasonal cluster frequency. Tentative estimations of central European temperature changes based solely on seasonal cluster frequencies can explain between 33.9% (summer) and 59.0% (winter) of temperature variance on the seasonal time scale. However, the signs of long-term changes in temperature are correctly reproduced even on multidecadal–centennial time scales. Moreover, linear warming trends are reproduced, implying from one-third up to one-half of the observed temperature increase between 1851/52 and 2003 (except for summer, but with significant trends for spring and autumn), indicating that changes in daily circulation patterns contribute to the observed overall long-term warming in the central European region.

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T. J. Ansell, P. D. Jones, R. J. Allan, D. Lister, D. E. Parker, M. Brunet, A. Moberg, J. Jacobeit, P. Brohan, N. A. Rayner, E. Aguilar, H. Alexandersson, M. Barriendos, T. Brandsma, N. J. Cox, P. M. Della-Marta, A. Drebs, D. Founda, F. Gerstengarbe, K. Hickey, T. Jónsson, J. Luterbacher, Ø. Nordli, H. Oesterle, M. Petrakis, A. Philipp, M. J. Rodwell, O. Saladie, J. Sigro, V. Slonosky, L. Srnec, V. Swail, A. M. García-Suárez, H. Tuomenvirta, X. Wang, H. Wanner, P. Werner, D. Wheeler, and E. Xoplaki

Abstract

The development of a daily historical European–North Atlantic mean sea level pressure dataset (EMSLP) for 1850–2003 on a 5° latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°–70°N, 70°W–50°E blended with marine data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The EMSLP fields for 1850–80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r2) indicate that EMSLP generally captures 80%–90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European–North Atlantic region, such as the 2003 heat wave, in the context of historical events.

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B. Wolf, C. Chwala, B. Fersch, J. Garvelmann, W. Junkermann, M. J. Zeeman, A. Angerer, B. Adler, C. Beck, C. Brosy, P. Brugger, S. Emeis, M. Dannenmann, F. De Roo, E. Diaz-Pines, E. Haas, M. Hagen, I. Hajnsek, J. Jacobeit, T. Jagdhuber, N. Kalthoff, R. Kiese, H. Kunstmann, O. Kosak, R. Krieg, C. Malchow, M. Mauder, R. Merz, C. Notarnicola, A. Philipp, W. Reif, S. Reineke, T. Rödiger, N. Ruehr, K. Schäfer, M. Schrön, A. Senatore, H. Shupe, I. Völksch, C. Wanninger, S. Zacharias, and H. P. Schmid

Abstract

ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

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Christiane Voigt, Ulrich Schumann, Andreas Minikin, Ahmed Abdelmonem, Armin Afchine, Stephan Borrmann, Maxi Boettcher, Bernhard Buchholz, Luca Bugliaro, Anja Costa, Joachim Curtius, Maximilian Dollner, Andreas Dörnbrack, Volker Dreiling, Volker Ebert, Andre Ehrlich, Andreas Fix, Linda Forster, Fabian Frank, Daniel Fütterer, Andreas Giez, Kaspar Graf, Jens-Uwe Grooß, Silke Groß, Katharina Heimerl, Bernd Heinold, Tilman Hüneke, Emma Järvinen, Tina Jurkat, Stefan Kaufmann, Mareike Kenntner, Marcus Klingebiel, Thomas Klimach, Rebecca Kohl, Martina Krämer, Trismono Candra Krisna, Anna Luebke, Bernhard Mayer, Stephan Mertes, Sergej Molleker, Andreas Petzold, Klaus Pfeilsticker, Max Port, Markus Rapp, Philipp Reutter, Christian Rolf, Diana Rose, Daniel Sauer, Andreas Schäfler, Romy Schlage, Martin Schnaiter, Johannes Schneider, Nicole Spelten, Peter Spichtinger, Paul Stock, Adrian Walser, Ralf Weigel, Bernadett Weinzierl, Manfred Wendisch, Frank Werner, Heini Wernli, Martin Wirth, Andreas Zahn, Helmut Ziereis, and Martin Zöger

Abstract

The Midlatitude Cirrus experiment (ML-CIRRUS) deployed the High Altitude and Long Range Research Aircraft (HALO) to obtain new insights into nucleation, life cycle, and climate impact of natural cirrus and aircraft-induced contrail cirrus. Direct observations of cirrus properties and their variability are still incomplete, currently limiting our understanding of the clouds’ impact on climate. Also, dynamical effects on clouds and feedbacks are not adequately represented in today’s weather prediction models.

Here, we present the rationale, objectives, and selected scientific highlights of ML-CIRRUS using the G-550 aircraft of the German atmospheric science community. The first combined in situ–remote sensing cloud mission with HALO united state-of-the-art cloud probes, a lidar and novel ice residual, aerosol, trace gas, and radiation instrumentation. The aircraft observations were accompanied by remote sensing from satellite and ground and by numerical simulations.

In spring 2014, HALO performed 16 flights above Europe with a focus on anthropogenic contrail cirrus and midlatitude cirrus induced by frontal systems including warm conveyor belts and other dynamical regimes (jet streams, mountain waves, and convection). Highlights from ML-CIRRUS include 1) new observations of microphysical and radiative cirrus properties and their variability in meteorological regimes typical for midlatitudes, 2) insights into occurrence of in situ–formed and lifted liquid-origin cirrus, 3) validation of cloud forecasts and satellite products, 4) assessment of contrail predictability, and 5) direct observations of contrail cirrus and their distinction from natural cirrus. Hence, ML-CIRRUS provides a comprehensive dataset on cirrus in the densely populated European midlatitudes with the scope to enhance our understanding of cirrus clouds and their role for climate and weather.

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