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Stefan Schneider, Yong Wang, Wolfgang Wagner, and Jean-Francois Mahfouf

Abstract

In this study, remotely sensed soil moisture data from the Advanced Scatterometer (ASCAT) on board the Meteorological Operational (MetOp) series of satellites are assimilated in the regional forecasting model, Aire Limitée Adaptation Dynamique Développement International (ALADIN-Austria), using a simplified extended Kalman filter. A pointwise bias correction method is applied to the ASCAT data as well as quality flags prepared by the data provider. The ASCAT assimilation case study is performed over central Europe during a 1-month period in July 2009. Forecasts of those assimilation experiments are compared to the control run provided by the operational ALADIN version of the Austrian Met Service, Zentralanstalt für Meteorologie und Geodynamik (ZAMG). Forecasts are furthermore verified versus in situ data. For a single-day case study the ability of the approach to improve precipitation forecast quality in the presence of high impact weather is demonstrated. Results show that 1) based on a one station in situ data evaluation, soil moisture analysis is improved, compared to the operational analysis, when ASCAT soil moisture data is assimilated; 2) pointwise bias correction of the satellite data is beneficial for forecast quality; 3) screen level parameter forecasts can be slightly improved as a result of this approach; and 4) convective precipitation forecast is improved over flatland for the investigation period while over mountainous regions the impact is neutral.

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Jasmin Vural, Stefan Schneider, Bernhard Bauer-Marschallinger, and Klaus Haslinger

Abstract

The proper determination of soil moisture on different scales is important for applications in a variety of fields. We aim to develop a high-level soil moisture product with high temporal and spatial resolution by assimilating the multilayer soil moisture product SCATSAR-SWI (Scatterometer Synthetic Aperture Radar Soil Water Index) into the surface model SURFEX. In addition, we probe the impact of the findings on the NumericalWeather Prediction (NWP) in Austria. The data assimilation system consists of the NWP model AROME and the SURFEX Offline Data Assimilation, which provide atmospheric forcing and soil moisture fields as mutual input. To address the known sensitivity of the employed simplified Extended Kalman Filter to the specification of errors, we compute the observation error variances of the SCATSAR-SWI locally using Triple Collocation Analysis and implement them into the assimilation system. The verification of the forecasted 2 m temperature and relative humidity against measurements of Austrian weather stations shows that the actual impact of the local error approach on the atmospheric forecast is slightly positive to neutral compared to the standard error approach, depending on the time of the year. The direct verification of the soil moisture analysis against a gridded water balance product reveals a degradation of the unbiased root mean square error for small observation errors.

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Benedikt Bica, Thomas Knabl, Reinhold Steinacker, Matthias Ratheiser, Manfred Dorninger, Christoph Lotteraner, Stefan Schneider, Barbara Chimani, Wolfgang Gepp, and Simon Tschannett

Abstract

Within the Vienna Enhanced Resolution Analysis (VERA) Climatology (VERACLIM) project, the complex influence of topographic structures on the spatial distribution of meteorological parameters has been investigated and evaluated climatologically. VERACLIM is aimed to generate a set of high-resolution analyses (lower meso-β-scale) of various meteorological parameters on a climatological basis. It tried to combine both the high spatial resolution provided by the VERA scheme that was used and the high temporal resolution of a comprehensive synoptic dataset of the last two decades, which was retrieved from ECMWF’s Meteorological Archival and Retrieval System (MARS). In the present study, the interpolated fields of reduced pressure of 3-hourly synoptic data over the Alpine region are evaluated climatologically. Using high temporal and spatial resolution, the authors were able to investigate both thermally and dynamically induced mesoscale pressure phenomena such as “Stau,” associated with trans-Alpine flows, blocking by the Alps, and local pressure extrema, as well as thermal lows and thermal high pressure zones. Comparisons are made between the mean course of reduced pressure at given grid points and the averaged divergence of the 10-m wind field in the Alpine region. It is shown that, climatologically, Alpine pumping and thermally induced pressure patterns have a similar frequency and intensity. For the latter ones, the buildup and cutback processes are described. Moreover, the frequency and intensity of pressure-related mesoscale features in the Alpine region over the last decades are investigated.

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Reinhold Steinacker, Matthias Ratheiser, Benedikt Bica, Barbara Chimani, Manfred Dorninger, Wolfgang Gepp, Christoph Lotteraner, Stefan Schneider, and Simon Tschannett

Abstract

A mesoscale data analysis method for meteorological station reports is presented. Irregularly distributed measured values are combined with measurement-independent a priori information about the modification of analysis fields due to topographic forcing. As a physical constraint to a thin-plate spline interpolation, the so-called “fingerprint method” recognizes patterns of topographic impact in the data and allows for the transfer of information to data-sparse areas. The results of the method are small-scale interpolation fields on a regular grid including topographically induced patterns that are not resolved by the station network. Presently, the fingerprint method is designed for the analysis of scalar meteorological variables like reduced pressure or air temperature. The principles for the fingerprint technique are based on idealized influence fields. They are calculated for thermal and dynamic surface forcing. For the former, the effects of reduced air volumes in valleys, the elevated heat sources, and the stability of the valley atmosphere are taken into account. The increase of temperature under ideal conditions in comparison to flat terrain is determined on a 1-km grid using height and surface geometry information. For the latter, a perturbation of an originally constant cross-Alpine temperature gradient is calculated by a topographical weighting. As a result, the gradient is steep where the mountain range is high and steep. If, during the interpolation process, some signal of the idealized patterns is found in the station data, it is used to downscale the analysis. It is shown by a cross validation of a case study that the interpolation of a mean sea level pressure field over the Alpine region is improved objectively by the method. Thermally induced mesoscale patterns are visible in the interpolated pressure field.

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Ulf Büntgen, Miroslav Trnka, Paul J. Krusic, Tomáš Kyncl, Josef Kyncl, Jürg Luterbacher, Eduardo Zorita, Fredrik Charpentier Ljungqvist, Ingeborg Auer, Oliver Konter, Lea Schneider, Willy Tegel, Petr Štěpánek, Stefan Brönnimann, Lena Hellmann, Daniel Nievergelt, and Jan Esper

Abstract

Annually resolved and absolutely dated tree-ring chronologies are the most important proxy archives to reconstruct climate variability over centuries to millennia. However, the suitability of tree-ring chronologies to reflect the “true” spectral properties of past changes in temperature and hydroclimate has recently been debated. At issue is the accurate quantification of temperature differences between early nineteenth-century cooling and recent warming. In this regard, central Europe (CEU) offers the unique opportunity to compare evidence from instrumental measurements, paleomodel simulations, and proxy reconstructions covering both the exceptionally hot summer of 2003 and the year without summer in 1816. This study uses 565 Swiss stone pine (Pinus cembra) ring width samples from high-elevation sites in the Slovakian Tatra Mountains and Austrian Alps to reconstruct CEU summer temperatures over the past three centuries. This new temperature history is compared to different sets of instrumental measurements and state-of-the-art climate model simulations. All records independently reveal the coolest conditions in the 1810s and warmest after 1996, but the ring width–based reconstruction overestimates the intensity and duration of the early nineteenth-century summer cooling by approximately 1.5°C at decadal scales. This proxy-specific deviation is most likely triggered by inflated biological memory in response to reduced warm season temperature, together with changes in radiation and precipitation following the Tambora eruption in April 1815. While suggesting there exists a specific limitation in ring width chronologies to capture abrupt climate perturbations with increased climate system inertia, the results underline the importance of alternative dendrochronological and wood anatomical parameters, including stable isotopes and maximum density, to assess the frequency and severity of climatic extremes.

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Clemens Simmer, Insa Thiele-Eich, Matthieu Masbou, Wulf Amelung, Heye Bogena, Susanne Crewell, Bernd Diekkrüger, Frank Ewert, Harrie-Jan Hendricks Franssen, Johan Alexander Huisman, Andreas Kemna, Norbert Klitzsch, Stefan Kollet, Matthias Langensiepen, Ulrich Löhnert, A. S. M. Mostaquimur Rahman, Uwe Rascher, Karl Schneider, Jan Schween, Yaping Shao, Prabhakar Shrestha, Maik Stiebler, Mauro Sulis, Jan Vanderborght, Harry Vereecken, Jan van der Kruk, Guido Waldhoff, and Tanja Zerenner

Abstract

Most activities of humankind take place in the transition zone between four compartments of the terrestrial system: the unconfined aquifer, including the unsaturated zone; surface water; vegetation; and atmosphere. The mass, momentum, and heat energy fluxes between these compartments drive their mutual state evolution. Improved understanding of the processes that drive these fluxes is important for climate projections, weather prediction, flood forecasting, water and soil resources management, agriculture, and water quality control. The different transport mechanisms and flow rates within the compartments result in complex patterns on different temporal and spatial scales that make predictions of the terrestrial system challenging for scientists and policy makers. The Transregional Collaborative Research Centre 32 (TR32) was formed in 2007 to integrate monitoring with modeling and data assimilation in order to develop a holistic view of the terrestrial system. TR32 is a long-term research program funded by the German national science foundation Deutsche Forschungsgemeinschaft (DFG), in order to focus and integrate research activities of several universities on an emerging scientific topic of high societal relevance. Aiming to bridge the gap between microscale soil pores and catchment-scale atmospheric variables, TR32 unites research groups from the German universities of Aachen, Bonn, and Cologne, and from the environmental and geoscience departments of Forschungszentrum Jülich GmbH. Here, we report about recent achievements in monitoring and modeling of the terrestrial system, including the development of new observation techniques for the subsurface, the establishment of cross-scale, multicompartment modeling platforms from the pore to the catchment scale, and their use to investigate the propagation of patterns in the state and structure of the subsurface to the atmospheric boundary layer.

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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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