Aerosols act as cloud condensation nuclei (CCN) for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE). Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion) to AIE from region to region. Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS), the sixyear mean anthropogenic + dust AIE is −0.27Wm−2 and is greatest during the summer months (<−2.0Wm−2) during which aerosol concentrations (from both dust and anthropogenic sources) are greatest. Comparing AIE as a function of thin (LWP<20 gm−2) vs. thick (LWP≥20 gm−2) clouds under conditions of large scale ascent or decent at 850 hPa showed that AIE is greatest for thick clouds during periods of upward vertical motion. In the Bay of Bengal, AIE is negligible owing to less favorable atmospheric conditions, a lower concentration of aerosols, and a non-alignment of aerosol and cloud layers. In the eastern North Atlantic, AIE is weakly positive (+0.1Wm−2) with dust aerosol concentration being much greater than the anthropogenic or sea salt components. However, elevated dust in this region exists above the maritime cloud layers and does not have a hygroscopic coating, which occurs in AS, preventing the dust from acting as CCN and limiting AIE. The Western Atlantic has a large anthropogenic aerosol concentration transported from the eastern United States producing a modest anthropogenic AIE (−0.46Wm−2). Anthropogenic AIE is also present off the West African coast corresponding to aerosols produced from seasonal biomass burning (both natural and man-made). Interestingly, atmospheric conditions are not particularly favorable for cloud formation compared to the other regions during the times where AIE is observed; however, clouds are generally thin (LWP<20 gm−2) and concentrated very near the surface. Overall, we conclude that vertical motion, aerosol type, and aerosol layer heights do make a significant contribution to AIE and that these factors are often more important than total aerosol concentration alone and that the relative importance of each differs significantly from region to region.

Aerosol indirect effects are considered to be the most uncertain yet important anthropogenic forcing of climate change. The goal of the present study is to reduce this uncertainty by constraining two different general circulation models (LMDZ and ECHAM4) with satellite data. We build a statistical relationship between cloud droplet number concentration and the optical depth of the fine aerosol mode as a measure of the aerosol indirect effect using MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data, and constrain the model parameterizations to match this relationship. We include here “empirical” formulations for the cloud albedo effect as well as parameterizations of the cloud lifetime effect. When fitting the model parameterizations to the satellite data, consistently in both models, the radiative forcing by the combined aerosol indirect effect is reduced considerably, down to −0.5 and −0.3Wm−2, for LMDZ and ECHAM4, respectively.

Several studies have claimed to have found significant weekly cycles of meteorological variables appearing over large domains, which can hardly be related to urban effects exclusively. Nevertheless, there is still an ongoing scientific debate whether these large-scale weekly cycles exist or not, and some other studies fail to reproduce them with statistical significance. In addition to the lack of the positive proof for the existence of these cycles, their possible physical explanations have been controversially discussed during the last years. In this work we review the main results about this topic published during the recent two decades, including a summary of the existence or non-existence of significant weekly weather cycles across different regions of the world, mainly over the US, Europe and Asia. In addition, some shortcomings of common statistical methods for analyzing weekly cycles are listed. Finally, a brief summary of supposed causes of the weekly cycles, focusing on the aerosol-cloud-radiation interactions and their impact on meteorological variables as a result of the weekly cycles of anthropogenic activities, and possible directions for future research, is presented.

Clouds regulate the Earth’s radiation budget, both by reflecting part of the incoming sunlight leading to cooling and by absorbing and emitting infrared radiation which tends to have a warming effect. Globally averaged, at the top of the atmosphere the cloud radiative effect is to cool the climate, while at the Arctic surface, clouds are thought to be warming. Here we compare a passive instrument, the AVHRR-based retrieval from CM-SAF, with recently launched active instruments onboard CloudSat and CALIPSO and the widely used ERA-Interim reanalysis. We find that in particular in winter months the three data sets differ significantly. While passive satellite instruments have serious difficulties, detecting only half the cloudiness of the modeled clouds in the reanalysis, the active instruments are in between. In summer, the two satellite products agree having monthly means of 70–80 percent, but the reanalysis are approximately ten percent higher. The monthly mean long- and shortwave components of the surface cloud radiative effect obtained from the ERAInterim reanalysis are about twice that calculated on the basis of CloudSat’s radar-only retrievals, while ground based measurements from SHEBA are in between. We discuss these differences in terms of instrument-, retrieval- and reanalysis characteristics, which differ substantially between the analyzed datasets.

A weekly cycle in aerosol pollution and some meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloudradiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol processes and cloud microphysics. It is found that the simulated weekly cycles in sulfur dioxide, sulfate, and aerosol optical depth in both models agree reasonably well with those observed indicating model skill in simulating the aerosol cycle. A distinct weekly cycle in cloud droplet number concentration is demonstrated in both observations and models. For other variables, such as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation fluxes, precipitation, and surface temperature, large variability and contradictory results between observations, model simulations, and model control simulations without a weekly cycle in emissions prevent us from reaching any firm conclusions about the potential aerosol impact on meteorology or the realism of the modelled second aerosol indirect effects.

Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather similar, about −0.6Wm−2 to −0.7Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change in net shortwave forcing in the models due to varying the autoconversion scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model “noise”. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from −0.3Wm−2 to −1.4Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and tau a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.

Globalmodelle sind aufgrund ihres groben Gitters (60 x 60 km) nur unzureichend in der Lage kleinskalige Prozesse (orographische Niederschlagsverstärkung) in der Atmosphäre aufzulösen. Mit Mesoskalenmodellen z.B. dem GESIMA (5 x 5 km) können deshalb die physikalische Grundlagen der Atmosphäre (Wolken- und Niederschlagsbildung) besser studiert und eine Kopplung mit hydrologischen Abflussmodellen erprobt werden. Zukünftig sieht dieses Projekt genau das vor, wobei der erste Teil, die Arbeit mit dem meteorologische Modell hier vorgestellt werden soll. Starkniederschlagserreignisse sind vielerorts auf der Welt mit charakteristischen Wetterlagen verbunden, die quasi über Tage unverändert ergiebigen Regen produzieren. Initialisiert mit den lokalen Vertikalprofilen aus Radiosondendaten, produzieren das prognostische Mesoskalenmodell GESIMA und das diagnostische Niederschlagsberechungsverfahren (MAXRR) maximale Regenmengen vergleichbarer Größenordnung. / Global models are insufficient to solve small scale atmospheric processes (e.g. orographic precipitation) due to their gross resolution (60 x 60 km). With mesoscale models e.g. the GESIMA (5 x 5 km), the physical fundamentals of the atmosphere (formation of precipitation and clouds) can better be studied and a coupling with hydrological models be tested through. This project plans exactly, as a first step, the work with the cited meteorological model. Heavy rainfall events are connected with characteristic weather conditions in many places in the world which produce invariably rain quasi over days. Initialized with the local vertical profiles from radiosonde data, the prediction model GESIMA and the diagnostic model MAXRR produced rain quantities of comparable order of magnitude.

Das Lokalmodell (LM) wurde für eine Reihe von Sensitivitätsuntersuchungen bezüglich orografischer Beeinflussung von Niederschlag verwendet. Für die Initialisierung des Modells mit Anfangs- und Randdaten wurde ein Schema entwickelt, welches eine horizontal homogene und stationäre Strömung aus einem einzelnen Vertikalprofil der benötigten atmosphärischen Variablen erstellt. Dabei wird hier auch der horizontale Luftdruckgradient berücksichtigt, wodurch eventuelle Auswirkungen der Coriolisterme auch ohne eine sehr große Entfernung des Zielgebietes vom Modellrand untersucht werden können. Simulationen mit idealisierten Eingangsfeldern können zur Verdeutlichung des Einflusses eines orografischen Hindernisses auf das dreidimensionale Strömungsfeld dienen. Außerdem sind sie zur Validierung bestimmter Parametrisierungen geeignet, da sich im Gegensatz zu realen Randdaten keine überlagerten synoptisch-skaligen Störungen im Modellgebiet befinden. Die hier verwendete Konvektionsparametrisierung nach Tiedtke (1989) zeigt unterschiedlich ausgeprägte Niederschlagsverteilungen und Flächenmittel in Abhängigkeit von der unterliegenden Orografie. / The Lokalmodell (LM) has been used for a series of sensitivity studies treating orographic modification of precipitation. An initialization technique has been developed which generates a horizontally homogeneous and stationary flow out of a single vertical profile of the required atmospheric variables. Herein, the horizontal pressure gradient is considered as well, allowing to investigate the influence of the Coriolis terms without the need for the area under investigation to be far away from the model boundaries. Simulations with idealized initialization fields can help to illustrate the influence of orographic obstacles on the three-dimensional flow field. Furthermore, they enable to validate certain parameterizations because of the missing synoptic-scale disturbances, which are present using real boundary data. The chosen parameterization of convection after Tiedtke (1989) shows different distributions of precipitation and its area-averaged values depending on the underlying orography.

Mit Hilfe eines Zirkulationsmodells der mittleren Atmosphäre wird die Ausbreitung der Quasi-Zwei-Tage-Welle simuliert. Das Modell verfügt über eine aktuelle Schwerewellenparametrisierung und ermöglicht daher die detaillierte Beschreibung der Wechselwirkung planetarer Wellen mit Schwerewellen. Bei Anwesenheit der Quasi-Zwei-Tage-Welle wird der Schwerewellenfluss mit der Periode von zwei Tagen und der räumlichen Struktur der Quasi- Zwei-Tage-Welle moduliert. Modellergebnisse zeigen, dass sich die Quasi-Zwei-Tage-Welle nicht gut in die untere Thermosphäre ausbreitet. Phasenvergleiche zwischen Quasi-Zwei-Tage-Welle und Divergenz des Eliassen-Palm-Flusses der Schwerewellen zeigen, dass dies eine Folge sekundärer Anregung der Quasi-Zwei-Tage-Welle durch brechende Schwerewellen ist, die außer Phase mit der Originalwelle erfolgt.