2015, Nunalee, C.G., Horváth, Á., Basu, S.

Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.

2011, Mikkonen, S., Romakkaniemi, S., Smith, J.N., Korhonen, H., Petäjä, T., Plass-Duelmer, C., Boy, M., McMurry, P.H., Lehtinen, K.E.J., Joutsensaari, J., Hamed, A., Mauldin III, R.L., Birmili, W., Spindler, G., Arnold, F., Kulmala, M., Laaksonen, A.

Gaseous sulphuric acid is a key precursor for new particle formation in the atmosphere. Previous experimental studies have confirmed a strong correlation between the number concentrations of freshly formed particles and the ambient concentrations of sulphuric acid. This study evaluates a body of experimental gas phase sulphuric acid concentrations, as measured by Chemical Ionization Mass Spectrometry (CIMS) during six intensive measurement campaigns and one long-term observational period. The campaign datasets were measured in Hyytiälä, Finland, in 2003 and 2007, in San Pietro Capofiume, Italy, in 2009, in Melpitz, Germany, in 2008, in Atlanta, Georgia, USA, in 2002, and in Niwot Ridge, Colorado, USA, in 2007. The long term data were obtained in Hohenpeissenberg, Germany, during 1998 to 2000. The measured time series were used to construct proximity measures ("proxies") for sulphuric acid concentration by using statistical analysis methods. The objective of this study is to find a proxy for sulfuric acid that is valid in as many different atmospheric environments as possible. Our most accurate and universal formulation of the sulphuric acid concentration proxy uses global solar radiation, SO2 concentration, condensation sink and relative humidity as predictor variables, yielding a correlation measure (R) of 0.87 between observed concentration and the proxy predictions. Interestingly, the role of the condensation sink in the proxy was only minor, since similarly accurate proxies could be constructed with global solar radiation and SO2 concentration alone. This could be attributed to SO2 being an indicator for anthropogenic pollution, including particulate and gaseous emissions which represent sinks for the OH radical that, in turn, is needed for the formation of sulphuric acid.

2013, Wilms, H., Rapp, M., Hoffmann, P., Fiedler, J., Baumgarten, G.

The influence of gravity waves on noctilucent clouds (NLC) at ALOMAR (69° N) is analysed by relating gravity wave activity to NLC occurrence from common-volume measurements. Gravity wave kinetic energies are derived from MF-radar wind data and filtered into different period ranges by wavelet transformation. From the dataset covering the years 1999–2011, a direct correlation between gravity wave kinetic energy and NLC occurrence is not found, i.e., NLC appear independently of the simultaneously measured gravity wave kinetic energy. In addition, gravity wave activity is divided into weak and strong activity as compared to a 13 yr mean. The NLC occurrence rates during strong and weak activity are calculated separately for a given wave period and compared to each other. Again, for the full dataset no dependence of NLC occurrence on relative gravity wave activity is found. However, concentrating on 12 h of NLC detections during 2008, we do find an NLC-amplification with strong long-period gravity wave occurrence. Our analysis hence confirms previous findings that in general NLC at ALOMAR are not predominantly driven by gravity waves while exceptions to this rule are at least possible.

2014, Forkel, M., Carvalhais, N., Schaphoff, S., v. Bloh, W., Migliavacca, M., Thurner, M., Thonicke, K.

Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.

2006, Serafimovich, A., Zülicke, Ch., Hoffmann, P., Peters, D., Dalin, P., Singer, W.

We present an experimental and modelling study of a strong gravity wave event in the upper troposphere/lower stratosphere near the Scandinavian mountain ridge. Continuous VHF radar measurements during the MaCWAVE rocket and ground-based measurement campaign were performed at the Norwegian Andoya Rocket Range (ARR) near Andenes (69.3° N, 16° E) in January 2003. Detailed gravity wave investigations based on PSU/NCAR Fifth-Generation Mesoscale Model (MM5) data have been used for comparison with experimentally obtained results. The model data show the presence of a mountain wave and of an inertia gravity wave generated by a jet streak near the tropopause region. Temporal and spatial dependencies of jet induced inertia gravity waves with dominant observed periods of about 13 h and vertical wavelengths of ~4.5–5 km are investigated with wavelet transform applied on radar measurements and model data. The jet induced wave packet is observed to move upstream and downward in the upper troposphere. The model data agree with the experimentally obtained results fairly well. Possible reasons for the observed differences, e.g. in the time of maximum of the wave activity, are discussed. Finally, the vertical fluxes of horizontal momentum are estimated with different methods and provide similar amplitudes. We found indications that the derived positive vertical flux of the horizontal momentum corresponds to the obtained parameters of the jet-induced inertia gravity wave, but only at the periods and heights of the strongest wave activity.

2011, Fiedler, J., Baumgarten, G., Berger, U., Hoffmann, P., Kaifler, N., Lübken, F.-J.

Noctilucent clouds (NLC) have been measured by the Rayleigh/Mie/Raman-lidar at the ALOMAR research facility in Northern Norway (69° N, 16° E). From 1997 to 2010 NLC were detected during more than 1850 h on 440 different days. Colocated MF-radar measurements and calculations with the Leibniz-Institute Middle Atmosphere (LIMA-) model are used to characterize the background atmosphere. Temperatures as well as horizontal winds at 83 km altitude show distinct differences during NLC observations compared to when NLC are absent. The seasonally averaged temperature is lower and the winds are stronger westward when NLC are detected. The wind separation is a robust feature as it shows up in measurements as well as in model results and it is consistent with the current understanding that lower temperatures support the existence of ice particles. For the whole 14-year data set there is no statistically significant relation between NLC occurrence and solar Lyman-α radiation. On the other hand NLC occurrence and temperatures at 83 km show a significant anti-correlation, which suggests that the thermal state plays a major role for the existence of ice particles and dominates the pure Lyman-α influence on water vapor during certain years. We find the seasonal mean NLC altitudes to be correlated to both Lyman-α radiation and temperature. NLC above ALOMAR are strongly influenced by atmospheric tides. The cloud water content varies by a factor of 2.8 over the diurnal cycle. Diurnal and semidiurnal amplitudes and phases show some pronounced year-to-year variations. In general, amplitudes as well as phases vary in a different manner. Amplitudes change by a factor of more than 3 and phases vary by up to 7 h. Such variability could impact long-term NLC observations which do not cover the full diurnal cycle.

2013, Pappalardo, G., Mona, L., D'Amico, G., Wandinger, U., Adam, M., Amodeo, A., Ansmann, A., Apituley, A., Alados Arboledas, L., Balis, D., Boselli, A., Bravo-Aranda, J.A., Chaikovsky, A., Comeron, A., Cuesta, J., De Tomasi, F., Freudenthaler, V., Gausa, M., Giannakaki, E., Giehl, H., Giunta, A., Grigorov, I., Groß, S., Haeffelin, M., Hiebsch, A., Iarlori, M., Lange, D., Linné, H., Madonna, F., Mattis, I., Mamouri, R.-E., McAuliffe, M.A.P., Mitev, V., Molero, F., Navas-Guzman, F., Nicolae, D., Papayannis, A., Perrone, M.R., Pietras, C., Pietruczuk, A., Pisani, G., Preißler, J., Pujadas, M., Rizi, V., Ruth, A.A., Schmidt, J., Schnell, F., Seifert, P., Serikov, I., Sicard, M., Simeonov, V., Spinelli, N., Stebel, K., Tesche, M., Trickl, T., Wang, X., Wagner, F., Wiegner, M., Wilson, K.M.

The eruption of the Icelandic volcano Eyjafjallajökull in April–May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April–26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at http://www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at http://www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5–15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events.

2011, Massling, A., Niedermeier, N., Hennig, T., Fors, E.O., Swietlicki, E., Ehn, M., Hämeri, K., Villani, P., Laj, P., Good, N., McFiggans, G., Wiedensohler, A.

The performance of six custom-built Hygrocopicity-Tandem Differential Mobility Analyser (H-TDMA) systems was investigated in the frame of an international calibration and intercomparison workshop held in Leipzig, February 2006. The goal of the workshop was to harmonise H-TDMA measurements and develop recommendations for atmospheric measurements and their data evaluation. The H-TDMA systems were compared in terms of the sizing of dry particles, relative humidity (RH) uncertainty, and consistency in determination of number fractions of different hygroscopic particle groups. The experiments were performed in an air-conditioned laboratory using ammonium sulphate particles or an external mixture of ammonium sulphate and soot particles. The sizing of dry particles of the six H-TDMA systems was within 0.2 to 4.2% of the selected particle diameter depending on investigated size and individual system. Measurements of ammonium sulphate aerosol found deviations equivalent to 4.5% RH from the set point of 90% RH compared to results from previous experiments in the literature. Evaluation of the number fraction of particles within the clearly separated growth factor modes of a laboratory generated externally mixed aerosol was done. The data from the H-TDMAs was analysed with a single fitting routine to investigate differences caused by the different data evaluation procedures used for each H-TDMA. The differences between the H-TDMAs were reduced from +12/−13% to +8/−6% when the same analysis routine was applied. We conclude that a common data evaluation procedure to determine number fractions of externally mixed aerosols will improve the comparability of H-TDMA measurements. It is recommended to ensure proper calibration of all flow, temperature and RH sensors in the systems. It is most important to thermally insulate the aerosol humidification unit and the second DMA and to monitor these temperatures to an accuracy of 0.2 °C. For the correct determination of external mixtures, it is necessary to take into account size-dependent losses due to diffusion in the plumbing between the DMAs and in the aerosol humidification unit.

2014, Crippa, M., Canonaco, F., Lanz, V.A., Äijälä, M., Allan, J.D., Carbone, S., Capes, G., Ceburnis, D., Dall'Osto, M., Day, D.A., DeCarlo, P.F., Ehn, M., Eriksson, A., Freney, E., Hildebrandt Ruiz, L., Hillamo, R., Jimenez, J.L., Junninen, H., Kiendler-Scharr, A., Kortelainen, A.-M., Kulmala, M., Laaksonen, A., Mensah, A.A., Mohr, C., Nemitz, E., O'Dowd, C., Ovadnevaite, J., Pandis, S.N., Petäjä, T., Poulain, L., Saarikoski, S., Sellegri, K., Swietlicki, E., Tiitta, P., Worsnop, D.R., Baltensperger, U., Prévôt, A.S.H.

Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.

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.