Among anthropogenic perturbations of the Earth\''s atmosphere, greenhouse gases and aerosols are considered to have a major impact on the energy budget through their impact on radiative fluxes. We use three ensembles of simulations with the LMDZ general circulation model to investigate the radiative impacts of five species of greenhouse gases (CO2, CH4, N2O, CFC-11 and CFC-12) and sulfate aerosols for the period 1930-1989. Since our focus is on the atmospheric changes in clouds and radiation from greenhouse gases and aerosols, we prescribed sea surface temperatures in these simulations. Besides the direct impact on radiation through the greenhouse effect and scattering of sunlight by aerosols, strong radiative impacts of both perturbations through changes in cloudiness are analysed. The increase in greenhouse gas concentration leads to a reduction of clouds at all atmospheric levels, thus decreasing the total greenhouse effect in the longwave spectrum and increasing absorption of solar radiation by reduction of cloud albedo. Increasing anthropogenic aerosol burden results in a decrease in high-level cloud cover through a cooling of the atmosphere, and an increase in the low-level cloud cover through the second aerosol indirect effect. The trend in low-level cloud lifetime due to aerosols is quantified to 0.5 min day-1 decade-1 for the simulation period. The different changes in high (decrease) and low-level (increase) cloudiness due to the response of cloud processes to aerosols impact shortwave radiation in a contrariwise manner, and the net effect is slightly positive. The total aerosol effect including also the aerosol direct and first indirect effects remains strongly negative.

Strategies to detect and attribute aerosol global impacts on clouds and climate from synergetic approaches involving modeling and observational evidence at different spatial and temporal scales.

Parameterisations of fractional cloudiness in large-scale atmospheric models rely on information about the subgrid-scale variablity of the total water specific humidity, qt , provided in form of a probability density function (PDF). In this contribution, four different approaches to evaluate such total-water PDFs are discussed: (i) Satellite spectroradiometers with high spatial resolution allow to construct at the scale of model grid boxes a histogram, and subsequently to derive the moments of the PDF, of the vertical integral of qt . This can be compared to the same quantity diagnosed from the model parameterisation. Although the vertical integral mostly focuses on the boundary layer, and involves issues in grid-boxes with orographic variability, it allowed nevertheless in the example presented to pinpoint deficiencies of a model parameterisation. (ii) Assuming a simple PDF shape and saturation within clouds, the simple “critical relative humidity” metric can be derived from infrared sounders and/or cloud lidar in combination with reanalysis data with a vertical resolution. It allows to evaluate the underlying PDF of any cloud scheme, but is sensitive to the assumptions. (iii) Supersites with a combination of ground-based lidar, radar and microwave data provide high-resolution high-quality reference data. In a “virtual reality” framework, we showed, however, that it is difficult to evaluate higher moments of a spatial PDF with this temporally-varying data. (iv) From a hierarchy of models from general circulation models to direct numerical simulations, we find that the variance of the qt follows a power-law scaling with an exponent of about -2. This information is very useful to improve the parameterisations.

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.

Variability and change of the Earth\''s climate are of fundamental importance to humankind. In particular anthropogenic climate change has been considered widely as one of the most urgent concerns for the society (United Nations, 1992, 2002). It is therefore vital to improve the understanding of the Earth\''s climate system and its variability.

Parameterization development and evaluation ideally takes a two-step approach (Lohmann et al., 2007). Insight into new processes, and initial parameterization formulation should be guided by theory, process-level observations (laboratory experiments or field studies) or, if these are unavailable, by high-resolution modelling. However, once implemented into large-scale atmospheric models, a thorough testing and evaluation is required in order to assure that the parameterization works satisfactorily for all weather situations and at the scales the model is applied to. Satellite observations are probably the most valuable source of information for this purpose, since they offer a large range of parameters over comparatively long time series and with a very large, to global, coverage. However, satellites usually retrieve parameters in a rather indirect way, and some quantities (e.g., vertical wind velocities) are unavailable. It is thus essential for model evaluation 1. to assure comparability; and, 2. to develop and apply metrics that circumvent the limitations of satellite observations and help to learn about parameterizations. In terms of comparability, the implementation of so-called \"satellite simulators\" has emerged as the approach of choice, in which satellite retrievals are emulated, making use of model information about the subgrid-scale variability of clouds, and creating summary statistics (Bodas-Salcedo et al., 2011; Nam and Quaas, 2012; Nam et al., 2014). In terms of process-oriented metrics, a large range of approaches has been developed, e.g. investigating the life cycle of cirrus from convective detrainment (Gehlot and Quaas, 2012), or focusing on the details of microphysical processes (Suzuki et al., 2011). Besides such techniques focusing on individual parameterizations, the data assimilation technique might be exploited, by objectively adjusting convection parameters and learning about parameter choices and parameterizations in this way (Schirber et al., 2013).In this chapter, we will first introduce the available satellite data, consider their limitations and the approaches to account for these, and then discuss observations-based process-oriented metrics that have been developed so far.

Meteor radar observations of mesosphere/lower thermosphere (MLT) daily temperatures have been performed at Collm, Germany since August 2004. The data have been analyzed with respect to long-period oscillations at time scales of 2–30 days. The results reveal that oscillations with periods of up to 6 days are more frequently observed during summer, while those with longer periods have larger amplitudes during winter. The oscillations may be considered as the signature of planetary waves. The results are compared with analyses from radar wind measurements. Moreover, the temperature oscillations show considerable year-to-year variability. In particular, amplitudes of the quasi 5-day oscillation have increased during the last decade, and the quasi 10-day oscillations are larger if the equatorial stratospheric winds are eastward.

The ionospheric response to solar extreme ultraviolet (EUV) variability during 2011–2014 is shown by simple proxies based on Solar Dynamics Observatory/Extreme Ultraviolet Variability Experiment solar EUV spectra. The daily proxies are compared with global mean total electron content (TEC) computed from global TEC maps derived from Global Navigation Satellite System dual frequency measurements. They describe about 74% of the intra-seasonal TEC variability. At time scales of the solar rotation up to about 40 days there is a time lag between EUV and TEC variability of about one day, with a tendency to increase for longer time scales.

Die Schriftenreihe gibt in 11 Fachbeiträgen die Ergebnisse aktueller Projekte und Forschungsvorhaben des LfULG wieder. Die Themen sind breit gefächert und beinhalten beim Grundwasser die Nitratbelastung an der Wasserfassung Diehsa, das Vorhaben eines digitalen Hydroisohypsenplanes in Sachsen, Sensor- und Thermo-Flowmetermessungen für den Ersatz von Grundwasseraufschlüssen sowie Informationen zum Projekt KLIWES mit Abschätzung der Auswirkungen der Klimaveränderungen auf den Wasserhaushalt in Sachsen. Die Themen des Altlastenbereiches umfassen neben dem Sächsischen Altlastenkataster die Schwerpunkte Sickerwasserprognose, Resorptionsverfügbarkeit von Schadstoffen aus Böden der Erzgebirgsregion, die Flutung der Grube Königstein und Informationen zum Projekt SUMATECS zur Anwendung sanfter Sanierungsverfahren. Die Vernetzung der einzelnen Fachdisziplinen wie z. B. bei Klimaänderungen oder der EU-Wasserrahmenrichtlinie (WRRL) spielt dabei eine immer größer werdende Rolle. »Grundwasser - Altlasten aktuell« erscheint mit dieser Ausgabe erstmals als Heft der Schriftenreihe.

In this thesis a novel approach to compare airborne observations of spectral upward and downward irradiances with along-track radiative transfer simulations (RTS) are presented. The RTS are performed with the ecRad radiation scheme of the Integrated Forecast System (IFS) operated by the European Centre for Medium Range Weather Forecast (ECMWF) and the library for Radiative transfer (libRadtran) on basis of hourly 0.1° IFS analysis data (IFS AD). The comparison aims to investigate the general capability of the utilized models to reproduce the observed radiation field. Simultaneous utilization of ecRad and libRadtran, driven by the same IFS AD, and comparison with observations enables to separate for potential errors in the applied IFS AD and ecRad.