Aktivitäten und Publikationen des Institut für Meteorologie der Universität Leipzig für 2002

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 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.

The distribution of model-based estimates of equilibrium climate sensitivity has not changed substantially in more than 30 years. Efforts to narrow this distribution by weighting projections according to measures of model fidelity have so far failed, largely because climate sensitivity is independent of current measures of skill in current ensembles of models. This work presents a cautionary example showing that measures of model fidelity that are effective at narrowing the distribution of future projections (because they are systematically related to climate sensitivity in an ensemble of models) may be poor measures of the likelihood that a model will provide an accurate estimate of climate sensitivity (and thus degrade distributions of projections if they are used as weights). Furthermore, it appears unlikely that statistical tests alone can identify robust measures of likelihood. The conclusions are drawn from two ensembles: one obtained by perturbing parameters in a single climate model and a second containing the majority of the world’s climate models. The simple ensemble reproduces many aspects of the multimodel ensemble, including the distributions of skill in reproducing the present-day climatology of clouds and radiation, the distribution of climate sensitivity, and the dependence of climate sensitivity on certain cloud regimes. Weighting by error measures targeted on those regimes permits the development of tighter relationships between climate sensitivity and model error and, hence, narrower distributions of climate sensitivity in the simple ensemble. These relationships, however, do not carry into the multimodel ensemble. This suggests that model weighting based on statistical relationships alone is unfounded and perhaps that climate model errors are still large enough that model weighting is not sensible.

Global mean cloud feedbacks in ten atmosphere-only climate models are estimated in perturbed sea surface temperature (SST) experiments and the results compared to doubled CO2 experiments using mixed-layer ocean versions of these same models. The cloud feedbacks in any given model are generally not consistent: the sign of the net cloud radiative feedback may vary according to the experimental design. However, both sets of experiments indicate that the variation of the total climate feedback across the models depends primarily on the variation of the net cloud feedback. Changes in different cloud types show much greater consistency between the two experiments for any individual model and amongst the set of models analyzed here. This suggests that the SST perturbation experiments may provide useful information on the processes associated with cloud changes which is not evident when analysis is restricted to feedbacks defined in terms of the change in cloud radiative forcing.

In this study, we examine the time evolution of the relative contribution of sulfate aerosols and greenhouse gases to anthropogenic climate change. We use the new IPSL-CM4 coupled climate model for which the first indirect effect of sulfate aerosols has been calibrated using POLDER satellite data. For the recent historical period the sulfate aerosols play a key role on the temperature increase with a cooling effect of 0.5 K, to be compared to the 1.4 K warming due to greenhouse gas increase. In contrast, the projected temperature change for the 21st century is remarkably independent of the effects of anthropogenic sulfate aerosols for the SRES-A2 scenario. Those results are interpreted comparing the different radiative forcings, and can be extended to other scenarios. We also highlight that the first indirect effect of aerosol strongly depends on the land surface model by changing the cloud cover.

The indirect effects of anthropogenic aerosols are expected to cause a significant radiative forcing of the Earth’s climate whose magnitude, however, is still uncertain. Most climate models use parameterizations for the aerosol indirect effects based on so-called ‘‘empirical relationships’’ which link the cloud droplet number concentration to the aerosol concentration. New satellite datasets such as those from the POLDER and MODIS instruments are well suited to evaluate and improve such parameterizations at a global scale. We derive statistical relationships of cloud-top droplet radius and aerosol index (or aerosol optical depth) from satellite retrievals and fit an empirical parameterization in a general circulation model to match the relationships. When applying the fitted parameterizations in the model, the simulated radiative forcing by the first aerosol indirect effect is reduced by 50% as compared to our baseline simulation (down to -0.3 and -0.4 Wm-2 when using MODIS and POLDER satellite data, respectively).

In their contribution to PNAS, Penner et al. (1) used a climate model to estimate the radiative forcing by the aerosol first indirect effect (cloud albedo effect) in two different ways: first, by deriving a statistical relationship between the logarithm of cloud droplet number concentration, ln Nc, and the logarithm of aerosol optical depth, ln AOD (or the logarithm of the aerosol index, ln AI) for present-day and preindustrial aerosol fields, a method that was applied earlier to satellite data (2), and, second, by computing the radiative flux perturbation between two simulations with and without anthropogenic aerosol sources. They find a radiative forcing that is a factor of 3 lower in the former approach than in the latter [as Penner et al. (1) correctly noted, only their “inline” results are useful for the comparison].

Realistic simulations of clouds are of uppermost importance for climate modelling using general circulation models. Satellite data are well suited to evaluate model parametrizations. In this study we use the Laboratoire de Me´te´orologie Dynamique general circulation model (LMDZ). We evaluate the current LMDZ cloud phase parametrization, in which the repartition of condensed cloud water between liquid and ice is a function of the local temperature. Three parameters are used to derive a relation between liquid cloud water content and temperature, two of which are not physically based. We use the POLDER-1 satellite data to infer more realistic parameters by establishing statistical relationships between cloud top thermodynamical phase and cloud top temperature, consistently in both satellite data and model results. We then perform a multitude of short model integrations and derive a best estimate for the lowest local temperature where liquid water can exist in a cloud (Tice = -32°C in our parametrization). The other parameter which describes the shape of the transition between ice and liquid water is also estimated. A longer simulation has then been performed with the new parameters, resulting in an improvement in the representation of the shortwave cloud radiative forcing.