Clouds and aerosols impact the Earth’s thermostat and precipitation. There is increasing evi- dence that dust aerosol frequently controls cloud glaciation, modifying clouds’ radiative eect and response to global warming. For realistic climate change projections, it is crucial to improve the simulated pathway between dust immersion freezing and cloud glaciation. However, current freezing schemes, which extrapolate laboratory results to larger atmospheric scales, are poorly constrained. Based on spaceborne observations of cloud-phase and aerosols, we explore whether dust-driven immersion freezing can be improved in a climate model so that the climate impact of dust ice-nuclei can be estimated more accurately. Combining an aerosol model reanalysis with spaceborne retrievals of cloud phase, we estimated the global co-variability between mineral dust aerosol and cloud glaciation. Relying on a spaceborne lidar, a lidar-radar synergy, and a radiometer-polarimeter synergy, we also locate and quantify the hemispheric and seasonal con- trast in cloud-phase. Finally, we use these estimations to refine the dust-driven droplet freezing in a climate model. Our results show that observations of cloud-top phase contrasts may be used to evaluate dust-driven droplet freezing in climate models. In the extratropics, the average frequency of ice cloud increases by +5% to +10% for higher mineral dust mixing-ratios on a day-to-day basis. For similar mixing-ratios of mineral dust, we found that the ice frequency can still vary between latitudes, especially between Hemispheres and between mid- and high-latitudes. By using only retrievals for which satellite products agree on cloud-phase, we find that the cloud-phase transition from liquid to ice occurs within a narrower temperature range. This suggests that individual products tend to classify too many clouds as liquid for temperatures below -30°C and too many as ice for temperatures above -10°C. At -30°C, the hemispheric and seasonal contrasts — relative to the Southern Hemisphere and boreal spring, respectively — lie between +21% to +39% for individual cloud- phase products and between +52% to +75% for a combination of products. We use these contrasts to tune the dust ice-nuclei eciency in the model, limiting their eect during clean conditions. Consequently, the model agrees better with the estimated cloud-top-phase contrasts and a dust-driven glaciation eect of 0.14 ± 0.13 W m^2 in the Northern Hemisphere, which is lower than previously assumed. These changes are associated with a decrease in the cloud liquid water path and a weak enhancement of the stratiform precipitation at the expense of convective precipitation. Our results show that observations of cloud-top phase contrasts may be used as a constraint for dust-driven droplet freezing in climate models. Thus, our constraining approach may help to achieve more accurate climate predictions and direct future climate model development. / Wolken und Aerosole beeinflussen den Energiehaushalt und den Wasserkreislauf der Erde. Es gibt zunehmend Hinweise darauf, dass Staubaerosol die Vereisung von Wolken, ihren Strahlungsef- fekt und ihre Antwort auf die globale Erwärmung beeinflusst. Um den Klimawandel genauer zu projizieren, ist es daher wichtig, den Weg von staubinduzierten Gefrierprozessen zur Vereisung der Wolken besser zu simulieren. Gegenwärtige Gefrierschemen, die von Laborergebnissen auf gröbere atmosphärische Skalen extrapolieren, sind jedoch limitiert in ihrer Anwendbarkeit. Basierend auf Satelliten-Beobachtungen von Wolkenphasen und Aerosolen wird in dieser Ar- beit untersucht, wie das staubbedingte Gefrieren in Klimamodellen verbessert werden kann, um Klimaeekte von Staubeiskeimen genauer abschätzen zu können. Zu diesem Zweck wer- den Reanalyse-Daten eines Aerosolmodells mit dem Satelliten-Beobachtungen von Wolkenphase kombiniert und die globale Kovariabilität zwischen Mineralstaubaerosol und Wolkenvereisung abgeschätzt. Basierend auf einem weltraumgestützten Lidar, einer Lidar-Radar Kombination und einer Radiometer-Polarimeter Kombination werden hemisphärische und saisonalen Kon- traste in der Wolkenphase lokalisiert und quantifiziert. Schließlich werden diese Schätzungen verwendet, um den Einfluss des Mineralstaubes auf das Gefrieren von Wolkentröpfchen in einem Klimamodell einzugrenzen. Die vorgelegten Ergebnisse zeigen, dass Beobachtungen des Kon- trastes in der Wolkenphase dafür verwendet werden können, das staubgetriebene Gefrieren von Wolkentröpfchen in Klimamodellen zu optimieren. In den Extratropen steigt die durchschnittliche Häufigkeit von Eiswolken für höhere Mineralstaub- Mischungsverhältnisse um +5% bis +10%. Bei ähnlichen Mischungsverhältnissen von Min- eralstaub kann die Häufigkeit von Eiswolken für verschiedene Breiten immer noch variieren. Einzelne Wolkenphasen-Produkte neigen dazu, zu viele Wolken als flüssig für Temperaturen unter -30°C und zu viele als Eis für Temperaturen über 10°C zu klassifizieren. Bei -30°C liegen die hemisphärischen und die saisonalen Kontraste — relativ zur südlichen Hemisphäre bzw. zum borealen Frühjahr — zwischen +21% und +39% für einzelne Produkte in der Wolken- phase und zwischen +52% und +75% für eine Kombination der Produkte. Diese Kontraste wurden verwendet, um die Ezienz der Staubeiskeime im Modell zu optimieren. Nach er- folgter Optimierung stimmt das Modell besser mit den aus Beobachtungen der geschätzten Kontraste in der Wolkenphase überein und zeigt einen staubbedingten nordhemisphärischen Netto-Strahlungseekt von 0.14 ± 0.13 W m^2 durch die Vereisung, der niedriger ist als bisher angenommen. Diese Änderungen sind mit einer Abnahme der Gesamtwassermenge in den Wolken und einer Verstärkung des stratiformen Niederschlags auf Kosten des konvektiven Niederschlags verbunden.

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.

An evaluation of a statistical cloud scheme taking into account subgrid-scale variability for water vapour and cloud condensate in the ECHAM5 general circulation model of the atmosphere is presented. Three-dimensional modelled water vapour, cloud liquid water and cloud ice were distributed stochastically into subcolumns of each grid box and vertically integrated to total water path (TWP). Thus the lower atmosphere is emphasized in the evaluation of TWP due to its exponential profile. The edited model dataset was compared with the globally analyzed distribution of TWP measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument. The results show that the mean TWP and mean cloud cover are on average relatively well simulated. However, large deficiencies are revealed by the evaluation of both variance and skewness of the probability density function (PDF). Systematically negative deviations of variance are found for almost all regions of the globe. Skewness of theTWPis overestimated in the Tropics and underestimated at high latitudes. Moreover, sensitivity experiments were performed to reveal the deficiencies in the parametrization leading to the observed deviations of variance and skewness of TWP. It was found that the positive bias in skewness in the Tropics can be reduced by modifying the influence of convection on the PDF.

The quasi two-day wave (QTDW) at 82–97km altitude over Collm (51° N, 13° E) has been observed using a VHF meteor radar. The long-term mean amplitudes calculated using data between September 2004 and August 2014 show a strong summer maximum 5 and a much weaker winter maximum. In summer, the meridional amplitude is slightly larger than the zonal one with about 15ms°1 at 91 km height. Phase differences are slightly greater than 90° on an average. The periods of the summer QTDW vary between 43 and 52H during strong bursts, while in winter the periods tend to be more diffuse. On an average, the summer QTDW is amplified after a maximum of 10 zonal wind shear which is connected with the summer mesospheric jet and there is a possible correlation of the summer mean amplitudes with the backgound wind shear. QTDW amplitudes exhibit considerable inter-annual variability, however, a clear relation between the 11 year solar cycle and the QTDW is not found.

The European Centre for Medium-range Weather Forecast (ECMWF) provides an aerosol re-analysis starting from year 2003 for the Monitoring Atmospheric Composition and Climate (MACC) project. The re-analysis assimilates total aerosol optical depth retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) to correct for model departures from observed aerosols. The reanalysis therefore combines satellite retrievals with the full spatial coverage of a numerical model. Re-analysed products are used here to estimate the shortwave direct and first indirect radiative forcing of anthropogenic aerosols over the period 2003–2010, using methods previously applied to satellite retrievals of aerosols and clouds. The best estimate of globally-averaged, all-sky direct radiative forcing is −0.7±0.3Wm−2. The standard deviation is obtained by a Monte-Carlo analysis of uncertainties, which accounts for uncertainties in the aerosol anthropogenic fraction, aerosol absorption, and cloudy-sky effects. Further accounting for differences between the present-day natural and pre-industrial aerosols provides a direct radiative forcing estimate of −0.4±0.3Wm−2. The best estimate of globally-averaged, all-sky first indirect radiative forcing is −0.6±0.4Wm−2. Its standard deviation accounts for uncertainties in the aerosol anthropogenic fraction, and in cloud albedo and cloud droplet number concentration susceptibilities to aerosol changes. The distribution of first indirect radiative forcing is asymmetric and is bounded by −0.1 and −2.0Wm−2. In order to decrease uncertainty ranges, better observational constraints on aerosol absorption and sensitivity of cloud droplet number concentrations to aerosol changes are required.

An increasing trend in surface solar radiation (solar brightening) has been observed over Europe since the 1990s, linked to economic developments and air pollution regulations and their direct as well as cloud-mediated effects on radiation. Here, we find that the all-sky solar brightening trend (1990–2005) over Europe from seven out of eight models (historical simulations in the Fifth Coupled Model Intercomparison Project) scales well with the regional and global mean effective forcing by anthropogenic aerosols (idealized “present-day” minus “preindustrial” runs). The reason for this relationship is that models that simulate stronger forcing efficiencies and stronger radiative effects by aerosol-cloud interactions show both a stronger aerosol forcing and a stronger solar brightening. The all-sky solar brightening is the observable from measurements (4.06 ± 0.60Wm−2 decade−1), which then allows to infer a global mean total aerosol effective forcing at about −1.30Wm−2 with standard deviation ±0.40Wm−2.

Large uncertainties exist in estimations of aerosol direct radiative forcing and indirect radiative forcing, and the values derived from globalmodeling differ substantially with satellite-based calculations. Following the approach of Quaas et al. (2008; hereafter named Quaas2008),we reassess satellite-based clear- and cloudy-sky radiative forcings and their seasonal variations by employing updated satellite products from 2004 to 2011 in combination with the anthropogenic aerosol optical depth (AOD) fraction obtained frommodel simulations using the Goddard Earth Observing System-Chemistry-Advanced ParticleMicrophysics (GEOS-Chem-APM). Our derived annual mean aerosol clear-sky forcing (-0.59 W m-2) is lower, while the cloudy-sky forcing (-0.34 W m-2) is higher than the corresponding results (-0.9Wm-2 and -0.2W m-2, respectively) reported in Quaas2008. Our study indicates that the derived forcings are sensitive to the anthropogenic AOD fraction and its spatial distribution but insensitive to the temporal resolution used to obtain the regression coefficients, i.e.,monthly or seasonal based. The forcing efficiency (i.e., the magnitude per anthropogenic AOD) for the clear-sky forcing based on this study is 19.9Wm-2, which is about 5% smaller than Quaas2008’s value of 21.1Wm-2. In contrast, the efficiency for the cloudy-sky forcing of this study (11 W m-2) is more than a factor of 2 larger than Quaas2008’s value of 4.7 W m-2. Uncertainties tests indicate that anthropogenic fraction of AOD strongly affects the computed forcings while using aerosol index instead of AOD from satellite data as aerosol proxy does not appear to cause any significant differences in regression slopes and derived forcings.

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.