To model clouds in the mesoscale a 3D nonhydrostatic numerical model - GESIMA - was used, with a new cloud scheme which includes a quasispectral treatment of 6 different bulk water species ( water vapor, cloud water, rain, ice, snow, graupel) . lt allows to predict the distribution parameters since the number concentration and the mass mixing ratio were prognosed. So it is possible to vary the average particle masses ( diameters) in time which gives more realistic results. According to measurements two different distribution functions (log-normal for rain and cloud water and Marshall-Palmer for solid water classes) were used to describe the different water species. The cloud model is tested in a simulation of a mesoscale snowfall event over the southern Baltic Sea. / Für die mesoskalige Simulation von Wolken wurde ein nichthydrostatisches numerisches 3D-Modell - GESIMA - benutzt, in dem ein neuer Wolkenmodul mit quasispektraler Behandlung 6 verschiedener Wolkenteilchenklassen (Wasserdampf, Wolkenwasser, Regen, Eis, Schnee, Graupel) implementiert wurde. Es erlaubt die Vorhersage der Verteilungsparameter, da sowohl die Teilchenzahlkonzentration als auch das Massenmischungsverhältnis prognostiziert werden. Damit ist es möglich auch die mittlere Masse (Durchmesser) einer Teilchensorte zeitlich zu variieren, was zu realistischeren Resultaten führt. In Übereinstimmung mit Messungen wurden 2 verschiedene Verteilungsfunktionen zur Beschreibung für die verschiedenen Teilchenklassen (log-normal für Wolkenwasser und Regen und Marshall-Palmer für Schnee und Graupel) benutzt. Das Wolkenmodell wurde in einer Simulation eines mesoskaligen Schneefallereignisses über der südwestlichen Ostsee getestet.

Three different boundary layer cloud models are incorporated into the ECHAM5 general circulation model (GCM) and compared to CloudSat and CALIPSO satellite observations. The first boundary layer model builds upon the standard Tiedtke (1989) parameterization for shallow convection with an adapted convective trigger; the second is a bulk parameterization of the effects of transient shallow cumulus clouds; and lastly the Dual Mass Flux (DMF) scheme adjusted to better represent shallow convection. The three schemes improved (Sub)Tropical oceanic low-level cloud cover, however, the fraction of low-level cloud cover remains underestimated compared to CALIPSO observations. The representation of precipitation was improved by all schemes as they reduced the frequency of light intensity events <0.01 mm d-1, which were found to dominate the radar reflectivity histograms as well as be the greatest source of differences between ECHAM5 and CloudSat radar reflectivity histograms. For both lidar and radar diagnostics, the differences amongst the schemes are smaller than the differences compared to observations. While the DMF approach remains experimental, as its top-of-atmosphere radiative balance has not been retuned, it shows the most promise in producing nonprecipitating boundary layer clouds. With its internally consistent boundary layer scheme that uses the same bimodal joint distribution with a diffusive and an updraft component for clouds and turbulent transport, the ECHAM5_DMF produces the most realistic boundary layer depth as indicated by the cloud field. In addition, it reduced the frequency of large-scale precipitation intensities of <0.01 mm d-1 the greatest.

The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately 22. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud Feedback Model Intercomparison Project’s Observation Simulator Package are used. Comparison of ECHAM5 with CALIPSO and CloudSat found large-scale features resolved by the model, such as the Hadley circulation, are captured well. The lidar simulator demonstrated ECHAM5 overestimates the amount of high-level clouds, particularly optically thin clouds. High-altitude clouds in ECHAM5 consistently produced greater lidar scattering ratios compared with CALIPSO. Consequently, the lidar signal in ECHAM5 frequently attenuated high in the atmosphere. The large scattering ratios were due to an underestimation of effective ice crystal radii in ECHAM5. Doubling the effective ice crystal radii improved the scattering ratios and frequency of attenuation. Additionally, doubling the effective ice crystal radii improved the detection of ECHAM5’s highest-level clouds by the radar simulator, in better agreement with CloudSat. ECHAM5 was also shown to significantly underestimate midlevel clouds and (sub)tropical low-level clouds. The low-level clouds produced were consistently perceived by the lidar simulator as too optically thick. The radar simulator demonstrated ECHAM5 overestimates the frequency of precipitation, yet underestimates its intensity compared with CloudSat observations. These findings imply compensating mechanisms inECHAM5 balance out the radiative imbalance caused by incorrect optical properties of clouds and consistently large hydrometeors in the atmosphere.

Global climate change is considered to be one of the most serious concerns of humankind (United Nations, 1992; United Nations, 2002). Anthropogenic greenhouse gases and aerosols impact considerably the energy balance of the Earth system, possibly provoking adverse effects on social, ecological, and economical equilibria. This is one of the main reasons why the understanding of the Earth’s climate system is of major importance. If better predictions of the response of the climate system to anthropogenic perturbations were available, political decisions against negative impacts could be taken, and social adaptations to changed climate conditions would be possible.

Im Rahmen dieser Dissertation wurden die mikrophysikalischen Eigenschaften von Aerosolpartikeln im Passatklima und deren Einfluss auf Passatwolken untersucht. Die Arbeit basiert auf Messungen mit der hubschrauber-getragenen Messplattform ACTOS. Es wurden zwei Intensivmesskampagnen im November 2010 und April 2011 durchgeführt, welche 31 Forschungsflüge in der Nähe der östlichsten Karibik-Insel Barbados umfassen. Die gemessenen Partikel-Anzahl-Größenverteilungen weisen meist eine bimodale Verteilung auf, welche typisch für marines Aerosol ist. Im Vergleich zu kontinentalen Verhältnissen ist die Totalanzahlkonzentration der Aerosolpartikel von 100-1000 cm-3 gering. Eine statistische Analyse einzelner Wolken lässt auf typische Anzahlkonzentrationen von aktivierten Partikeln bis zu 400 cm-3 und minimale Aktivierungsdurchmesser in der Größenordnung von 40 nm bis 180 nm mit entsprechenden maximalen kritischen Übersättigungen zwischen 0.1 und 0.9% schließen. Zusätzlich wurden wesentliche Einflussfaktoren auf die Anzahlkonzentration aktivierter Partikel identifiziert: 1) Vertikalwind an der Wolkenunterkante und 2) Anzahlkonzentration der verfügbaren Aerosolpartikel, die als Wolkenkondensationskeime dienen können. Mit Hilfe von Beobachtungsdaten und einer umfassenden Sensitivitätsstudie unter Verwendung eines Luftpaketmodells mit spektraler Wolkenmikrophysik wurde die Sensitivität der Wolkentropfenkonzentration gegenüber Änderungen in den physikalischen Eigenschaften und der Hygroskopizität von Aerosolpartikeln untersucht. Die beobachteten Ergebnisse in Form von sogenannten \"aerosol-cloud interaction metrics\" (ACI, Maß für den Einfluss von Änderungen einer bestimmten Aerosoleigenschaft auf eine bestimmte Wolkeneigenschaft) zeigen eine sehr hohe Sensitivität der Tropfenanzahlkonzentration gegenüber Änderungen in der Partikelanzahlkonzentration (in der Nähe des physikalisch sinnvollen Maximums von eins). Diese abgeleiteten ACI-Metriken eignen sich als Basis für Abschätzungen des indirekten Strahlungsantriebes auf der Grundlage von Beobachtungen. Zusätzliche Modellrechnungen umfassen die gemessenen Partikeleigenschaften während der gesamten Kampagnen. Die Ergebnisse unterstreichen besonders die Bedeutung der physikalischen Partikeleigenschaften. Die Suszeptibilität der Tropfenanzahlkonzentration gegenüber Änderungen in der Partikelanzahlkonzentration (Wertebereich: 0-1) ist am größten (> 0.9) für den Fall eines stark ausgeprägten Akkumulations-Mode und nimmt ab, je stärker der Aitken-Mode ausgeprägt ist (> 0.6). Im Gegensatz dazu ist die Sensitivität der Tropfenanzahlkonzentration gegenüber Änderungen in der Hygroskopizität der Partikel generell geringer (< 0.4). Die hier präsentierten Ergebnisse stellen eine umfangreiche Charakterisierung der Aerosol- und Wolkeneigenschaften im Passatklima dar und können helfen, die vorhergesagte Sensitivität der Wolkeneigenschaften in Klimamodellen gegenüber Änderungen der Aerosoleigenschaften zu evaluieren und deren Unsicherheiten zu reduzieren. / Within the scope of this dissertation, microphysical properties of aerosol particles in the trade wind regime and their influence on microphysical properties of trade wind cumulus clouds have been investigated. The study is based on measurements performed with the helicopter-borne measurement platform ACTOS. Two intensive measurement periods were carried out in November 2010 and April 2011, including 31 research flights close to the easternmost Caribbean island - Barbados. Aerosol particle number size distributions show a bimodal structure, which is typical for marine aerosol particles. The total particle concentrations of approximately 100-1000 cm-3 are compared to continental conditions relatively low. A statistical analysis of individual clouds reveals typical number concentrations of activated particles up to 400 cm-3 and minimum activation diameters between 40 and 180 nm with corresponding critical supersaturations between 0.1 and 1%. Additionally, major factors affecting the number concentration of activated particles are identifed: 1) vertical wind velocity at cloud base and, 2) number concentration of available aerosol particles as potential cloud condensation nuclei. With the help of observational data and a comprehensive sensitivity study using a spectral cloud microphysical parcel model, the sensitivity of the cloud droplet number concentration towards changes in the microphysical aerosol particle properties and their hygroscopicity has been investigated. Observational results in terms of so-called aerosol-cloud interactions metrics (describes a measure of the influence of changes in one specific aerosol property on one specific cloud property) show a very high sensitivity (close to the physical meaningful maximum of unity) of the number concentration of activated particles towards changes in the particle number concentration. These aerosol-cloud interaction metrics can be used as basis for observationally-based radiative forcing estimates. Additional model calculations cover the entire range of the observed aerosol properties during both campaigns. The results underline particularly the importance of the physical aerosol properties. The calculated susceptibility (valuation: 0-1) of the droplet number concentration towards changes in the particle number concentration is highest (> 0.9) for accumulation mode dominated particle number size distributions and decreases for Aitken mode dominated size distributions (> 0.6). In contrast, for the modeled parameter space, the sensitivity towards changes in the particle hygroscopicity is generally below 0.4. The findings presented in this study represent a comprehensive characterization of aerosol and cloud microphysical properties in the trade wind regime. These findings may help to evaluate the predicted sensitivity of cloud microphysical properties by climate models towards changes in particle microphysical properties and reduce the uncertainties in climate sensitivity estimates.

We present a method for deriving the radiative effects of absorbing aerosols in cloudy scenes from satellite retrievals only. We use data of 2005–2007 from various passive sensors aboard satellites of the “A-Train” constellation. The study area is restricted to the tropical- and subtropical Atlantic Ocean. To identify the dependence of the local planetary albedo in cloudy scenes on cloud liquid water path and aerosol optical depth (AOD), we perform a multiple linear regression. The OMI UV-Aerosolindex serves as an indicator for absorbing-aerosol presence. In our method, the aerosol influences the local planetary albedo through direct- (scattering and absorption) and indirect (Twomey) aerosol effects. We find an increase of the local planetary albedo (LPA) with increasing AOD of mostly scattering aerosol and a decrease of the LPA with increasing AOD of mostly absorbing aerosol. These results allow us to derive the direct aerosol effect of absorbing aerosols in cloudy scenes, with the effect of cloudy-scene aerosol absorption in the tropical- and subtropical Atlantic contributing (+21.2±11.1)×10−3 Wm−2 to the global top of the atmosphere radiative forcing.

Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the “perfect model approach.” This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.

A simple way to diagnose fractional cloud cover in general circulation models is to relate it to the simulated relative humidity, and allowing for fractional cloud cover above a “critical relative humidity” of less than 100%. In the formulation chosen here, this is equivalent to assuming a uniform “top-hat” distribution of subgrid-scale total water content with a variance related to saturation. Critical relative humidity has frequently been treated as a “tunable” constant, yet it is an observable. Here, this parameter, and its spatial distribution, is examined from Atmospheric Infrared Sounder (AIRS) satellite retrievals, and from a combination of relative humidity from the ECMWF Re-Analyses (ERA-Interim) and cloud fraction obtained from CALIPSO lidar satellite data. These observational data are used to evaluate results from different simulations with the ECHAM general circulation model (GCM). In sensitivity studies, a cloud feedback parameter is analyzed from simulations applying the original parameter choice, and applying parameter choices guided by the satellite data. Model sensitivity studies applying parameters adjusted to match the observations show larger positive cloud-climate feedbacks, increasing by up to 30% compared to the standard simulation.

Ship tracks are regarded as the most obvious manifestations of the effect of anthropogenic aerosol particles on clouds (indirect effect). However, it is not yet fully quantified whether there are climatically relevant effects on large scales beyond the narrow ship tracks visible in selected satellite images. A combination of satellite and reanalysis data is used here to analyze regions in which major shipping lanes cut through otherwise pristine marine environments in subtropical and tropical oceans. We expect the region downwind of a shipping lane is affected by the aerosol produced by shipping emissions but not the one upwind. Thus, differences in microphysical and macrophysical cloud properties are analyzed statistically. We investigate microphysical and macrophysical cloud properties as well as the aerosol optical depth and its fine-mode fraction for the years 2005–2007 as provided for by retrievals of the two Moderate Resolution Imaging Spectroradiometer instruments. Water-cloud properties include cloud optical depth, cloud droplet effective radius, cloud top temperature, and cloud top pressure. Large-scale meteorological parameters are taken from ERA-Interim reanalysis data and microwave remote sensing (sea surface temperature). We analyze the regions of interest in a Eulerian and Lagrangian sense, i.e., sampling along shipping lanes and sampling along wind trajectories, respectively. No statistically significant impacts of shipping emissions on large-scale cloud fields could be found in any of the selected regions close to major shipping lanes. In conclusion, the net indirect effects of aerosols from ship emissions are not large enough to be distinguishable from the natural dynamics controlling cloud presence and formation.