Petra Friederichs

• Dr. rer. nat.
• University of Bonn

The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate w...

The question to what extent climate change is responsible for extreme weather events has been at the forefront of public and scholarly discussion for years. Proponents of the "risk-based" approach to attribution attempt to give an unconditional answer based on the probability of some class of events in a world with and without human influences. As...

De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de...

ClimXtreme Bericht zur Hochwasserlage Dezember 23 / Januar 24

We present a method for the analysis and compact description of large-scale multivariate weather extremes. Spatial patterns of extreme events are identified using the tail pairwise dependence matrix (TPDM) proposed by Cooley and Thibaud (2019). We also introduce the cross-TPDM to identify patterns of common extremes in two variables. An extremal pa...

De-aliasing products are used in the estimation process of satellite-based gravity field computation to reduce errors from high-frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non-tidal atmosphere and oceanic mass variations at 3-hourly resolution. However, the model-based de...

The European continent is regularly affected by a wide range of extreme events and natural hazards including heatwaves, extreme precipitation, droughts, cold spells, windstorms, and storm surges. Many of these events do not occur as single extreme events, but rather show a multivariate character, the so-called compound events. Within the scope of t...

Doppler wind lidars (DWLs) have increasingly been used over the last decade to derive the mean wind in the atmospheric boundary layer. DWLs allow the determination of wind vector profiles with high vertical resolution and provide an alternative to classic meteorological tower observations. They also receive signals from altitudes higher than a towe...

Doppler wind lidars (DWLs) have increasingly been used over the last decade to derive the mean wind in the atmospheric boundary layer. DWLs allow the determination of wind vector profiles with high vertical resolution and provide an alternative to classic meteorological tower observations. They also receive signals from higher altitudes than a towe...

The verification of high-resolution meteorological models requires highly resolved validation data and appropriate tools of analysis. While much progress has been made in the case of precipitation, wind fields have received less attention, largely due to a lack of spatial measurements. Clear-sky radar echoes could be an unexpected part of the solut...

The verification of high-resolution meteorological models requires highly resolved validation data and appropriate tools of analysis. While much progress has been made in the case of precipitation, wind fields have received less attention, largely due to a lack of spatial measurements. Clear-sky radar echoes could be an unexpected part of the solut...

We use symbolic regression to estimate daily precipitation amounts at six stations in the Alpine region from a global reanalysis. Symbolic regression only prescribes the set of mathematical expressions allowed in the regression model, but not its structure. The regression models are generated by genetic programming (GP) in analogy to biological evo...

We present a revised local wavelet‐based organization index (LW), which is applied to both synthetic fields and meteorological fields of precipitation and brightness temperature for different types of convective organization. The LW consists of three components that describe the scale (LWsc), quantify the intensity (LWin), and analyze the anisotrop...

One important attribute of meteorological forecasts is their representation of spatial structures. While several existing verification methods explicitly measure a structure error, they mostly produce a single value with no simple interpretation. Extending a recently developed wavelet‐based verification method, this study separately evaluates the p...

Many applications require wind gust estimates at very different atmospheric height levels. For example, the renewable energy sector is interested in wind and gust predictions at the hub height of a wind power plant. However, numerical weather prediction models typically only derive estimates for wind gusts at the standard measurement height of 10 m...

Recently developed verification tools based on local wavelet spectra can isolate errors in the spatial structure of quantitative precipitation forecasts, thereby answering the question of whether the predicted rainfall variability is distributed correctly across a range of spatial scales. This study applies the wavelet-based structure scores to rea...

High‐resolution simulations (grid spacing 2.5 km) are performed with ICON‐LEM to characterize convective organization in the Tropics during August 2016 over a large domain ranging from northeastern South America, along the tropical Atlantic to Africa (8,000×3,000 km). The degree of organization is measured by a refined version of the wavelet‐based...

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve...

Abstract. Many applications require wind gust estimates at very different atmospheric height levels. For example, the renewable energy sector is interested in wind and gust predictions at the hub height of a wind power plant. However, numerical weather prediction models typically derive estimates for wind gusts at the standard measurement height of...

The assessment of long‐term trends in environmental extremes is a challenging and important subject in the current discussion on global climate change. We propose a new approach for evaluating temporal trends and spatial homogeneity in extremes accounting also for spatial dependence. Based on exceedances over a space–time threshold, we provide esti...

The quality of precipitation forecasts is difficult to evaluate objectively because images with disjointed features surrounded by zero intensities cannot easily be compared pixel by pixel: any displacement between observed and predicted fields is punished twice, generally leading to better marks for coarser models. To answer the question of whether...

The quality of precipitation forecasts is difficult to evaluate objectively because images with disjoint features surrounded by zero intensities cannot easily be compared pixel by pixel: Any displacement between observed and predicted field is punished twice, generally leading to better marks for coarser models. To answer the question whether a hig...

A suitable formulation of the rain drop size distribution (DSD) is a prerequisite for a successful assimilation of radar polarimetric information on rain into a numerical weather prediction model. Popular DSD parameterizations in two-moment bulk microphysics schemes use relations between the so-called mean-mass diameter [Formula: see text] and the...

The 7th International Verification Methods Workshop – with a theme of “forecast verification methods across time and space scales” – was held in Berlin between 3 and 11 May 2017. The workshop and associated training tutorial represent two flagship activities of the World Meteorological Organization's (WMO's) Joint Working Group on Forecast Verifica...

Wavelet spectra of rain rates are used to characterize convective organization in high‐resolution simulations (horizontal grid spacing 156 m) with the large‐eddy model ICON‐LEM over Germany. Scattered convection takes place on scales between 1.2 and 4.8 km, while organized structures like supercells or mesoscale convective systems act on scales abo...

The purpose of this study is to perform verification of the structural characteristics of high-resolution spatial forecasts without relying on an object identification algorithm. To this end, a wavelet approach developed for image texture analysis is applied to an ensemble of high-resolution quantitative precipitation forecasts. The forecasts are v...

Symbolic regression is used to estimate daily time series of local station precipitation amounts from global climate model output with a coarse spatial resolution. Local precipitation is of high importance in climate impact studies. Standard regression, minimizing the RMSE or a similar point-wise error, by design underestimates temporal variability...

With the recent advent of a sound mathematical theory for extreme events in dynamical systems, new ways of analyzing a system's inherent properties have become available: Studying only the probabilities of extremely close Poincar\'e recurrences, we can infer the underlying attractor's local dimensionality - a quantity which is closely linked to the...

With the recent advent of a sound mathematical theory for extreme events in dynamical systems, new ways of analyzing a system's inherent properties have become available: Studying only the probabilities of extremely close Poincar\'{e} recurrences, we can infer the underlying attractor's local dimensionality -- a quantity which is closely linked to...

The recently derived decomposition of the quantile score into uncertainty, resolution and reliability (Bentzien and Friederichs, 2014) can be generalized to a decomposition of the continuous ranked probability score (CRPS). This decomposition reveals detailed insights into ensemble performance in terms of calibration and information content. We uti...

Coupled models of the soil-vegetation-atmosphere systems are increasingly used to investigate interactions between the system components. Due to the different spatial and temporal scales of relevant processes and computational restrictions, the atmospheric model generally has a lower spatial resolution than the land surface and subsurface models. W...

A new approach for evaluating time-trends in extreme values accounting also for spatial dependence is proposed. Based on exceedances over a space-time threshold, estimators for a trend function and for extreme value parameters are given, leading to a homogenization procedure for then applying stationary extreme value processes. Extremal dependence...

The integration of physical relationships into stochastic models is of major interest e.g. in data assimilation. Here, a multivariate Gaussian random field formulation is introduced, which represents the differential relations of the two-dimensional wind field and related variables such as streamfunction, velocity potential, vorticity and divergenc...

The integration of physical relationships into stochastic models is of major interest e.g. in data assimilation. Here, a multivariate Gaussian random field formulation is introduced, which represents the differential relations of the two-dimensional wind field and related variables such as streamfunction, velocity potential, vorticity and divergenc...

To improve the forecasts of weather extremes, we propose a joint spatial model for the observations and the forecasts, based on a bivariate Brown-Resnick process. As the class of stationary bivariate Brown-Resnick processes is fully characterized by the class of pseudo cross-variograms, we contribute to the theorical understanding of pseudo cross-v...

PV elegantly describes synoptic- and planetary-scale dynamics, but it has received less attention on smaller scales. On the convective scale PV is characterised by dipoles associated with convective cells. We show that the PV dipoles are statistically significant and associated with statistically significant flow anomalies. Our hypothesis is that t...

Atmospheric reanalyses are a state-of-the-art tool to generate consistent and realistic state estimates of the atmospheric system. They provide a synthesis of various heterogeneous observational systems and model simulations using a physical model together with a data assimilation scheme. Current reanalyses are mainly global, while regional reanaly...

Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES c...

Due to the emergence of new high resolution numerical weather prediction (NWP) models and the availability of new or more reliable remote sensing data, the importance of efficient spatial verification techniques is growing. Wavelet transforms offer an effective framework to decompose spatial data into separate (and possibly orthogonal) scales and d...

Due to the emergence of new high resolution numerical weather prediction (NWP) models and the availability of new or more reliable remote sensing data, the importance of efficient spatial verification techniques is growing. Wavelet transforms offer an effective framework to decompose spatial data into separate (and possibly orthogonal) scales and d...

Based largely on an International Commission on Dynamical Meteorology (ICDM) workshop, this timely volume, written by leading researchers in the field, covers a range of important research issues related to high-impact weather and extreme climate events. Dynamical linkages between these extremes and various atmospheric and ocean phenomena are exami...

The feature based spatial verification method SAL is applied to cloud data, i.e. two-dimensional spatial fields of total cloud cover and spectral radiance. Model output is obtained from the COSMO-DE forward operator SynSat and compared to SEVIRI satellite data. The aim of this study is twofold. First, to assess the applicability of SAL to this kind...

The feature based spatial verification method SAL is applied to cloud data, i.e. two-dimensional spatial fields of total cloud cover and spectral radiance. Model output is obtained from the COSMO-DE forward operator SynSat and compared to SEVIRI satellite data. The aim of this study is twofold. First, to assess the applicability of SAL to this kind...

The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction,...

The main purpose of this study is to develop an easy-to-use weather generator (WG) for the downscaling of gridded data to point measurements at regional scale. The WG is applied to daily averaged temperatures and annual growing degree days (GDD) of wheat. This particular choice of variables is motivated by future investigations on temperature impac...

Potential vorticity (PV) and its conservation principle elegantly describe large-scale atmospheric dynamics. On the mesoscale, however, PV has received less attention. We describe the characteristics of PV on the convective weather scale (≈10 km) as simulated by the non-hydrostatic numerical weather prediction model COSMO-DE. Two weather cases with...

While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are introduced here, based on quantile forecasts being th...

Statistical methods to bias correct global or regional climate model output are now common to get data closer to observations in distribution. However, most bias correction (BC) methods work for one variable and one location at a time and basically reproduce the temporal structure of the models. The intervariable, spatial, and temporal dependencies...

A high-resolution regional reanalysis system for Europe and Germany has been developed by the climate monitoring branch of the Hans-Ertel-Centre for Weather Research. The system is based on DWD’s operational NWP system centered around the COSMO model. The reanalyses are driven by ERA-Interim as boundary conditions with two nesting steps. COSMO-REA6...

The WEX-MOP project aims at a next generation ensemble prediction system for the mesoscale. One goal of WEX-MOP is to quantify the role of conserved quantities during extreme convective weather. Conserved variables might offer new insight in the predictability of those events. An important conserved quantity is potential vorticity (PV), a fundament...

Atmospheric reanalyses covering the European region are mainly available as part of comparably coarse global reanalysis. The aim of this paper is to present the development and evaluation of a next generation regional reanalysis for the European CORDEX EUR-11 domain with a horizontal grid spacing of approximately 6 km. In this context, a reanalysis...

The work presented here comprises the setup and evaluation of a 30-year high-resolution reanalysis for the European CORDEX domain currently in production. Results are shown for two 5-year streams. As reanalyses gain more and more importance as a source of meteorological information for many purposes, global reanalyses provide high quality four-dime...

The coupling of models for the different components of the Soil-Vegetation-Atmosphere-System is required to investigate component interactions and feedback processes. However, the component models for atmosphere, land-surface and subsurface are usually operated at different resolutions in space and time owing to the dominant processes. The computat...

This study expands the pool of verification methods for probabilistic weather and climate predictions by a decomposition of the quantile score (QS). The QS is a proper score function and evaluates predictive quantiles on a set of forecast-observation pairs. We introduce a decomposition of the QS in reliability, resolution and uncertainty, and discu...

Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coeffi...

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts int...

Forecast verification for probabilistic weather and climate predictions gain more and more importance due to the increasing number of ensemble prediction systems. The predictive performance of probabilistic forecasts is generally assessed using proper score functions, which are applied to a set of forecast-observation pairs. The propriety of a scor...

The WEX-MOP project aims at a next generation ensemble prediction system for the mesoscale. One goal of WEX-MOP is to quantify the role of conserved quantities during extreme convective weather. Conserved variables might offer new insight in the predictability of those events. An important conserved quantity is potential vorticity (PV), a fundament...

The purpose of this study is to perform verification of the structural characteristics of high-resolution spatial forecasts without relying on an object identification algorithm. To this end, a wavelet approach developed for image texture analysis is applied to an ensemble of high-resolution quantitative precipitation forecasts. The forecasts are v...

In order to incorporate the dependence between the spatial random fields of observed and forecasted maximal wind gusts, we propose to model them jointly by a bivariate Brown-Resnick process. As there is a one-to-one correspondence between bivariate Brown-Resnick processes and pseudo cross-variograms, station- ary Brown-Resnick processes can be char...

The vertical structure of the atmosphere has large impact on mesoscale processes like convective storms and heavy precipitation events. Convective instabilities are governed by vertical profiles of temperature and humidity, and more precisely the equivalent potential temperature profile. Due to downdrafts within convective structures, surface wind...

Predictions of the uncertainty associated with extreme events are a vital component of any prediction system for such events. Consequently, the prediction system ought to be probabilistic in nature, with the predictions taking the form of probability distributions. This paper concerns probabilistic prediction systems where the data is assumed to fo...

Statistical postprocessing is an integral part of an ensemble prediction system. This study compares methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium for Small-Scale Modeling (COSMO-DE) time-lagged ensemble (COSMO-DE-TLE). The investigation covers the per...

Kinetic energy spectra derived from commercial aircraft observations of horizontal wind velocities exhibit a k –5/ 3 wavenumber dependence on the mesoscale that merges into a k –3 dependence on the macroscale. In this study, spectral analysis is applied to evaluate the mesoscale ensemble prediction system using the convection-permitting NWP model C...

Extremes in weather such as high wind speeds or heavy precipitation are associated with high impacts on both environment and society. It is thus of great importance to improve the quality of extreme wind and heavy precipitation forecasts. Numerical weather forecast models provide information about the general conditions in which extremes occur. How...

High-resolution limited-area numerical weather prediction (NWP) models are particularly developed in order to predict high-impact weather. Due to their high resolution of a few km and their non-hydrostatic dynamics, they are able to describe mesoscale processes in a more detailed and explicit way. Although high-resolution model forecasts lead to mo...

We review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic...

Present day weather forecast models usually cannot provide realistic descriptions of local and particularly extreme weather conditions. However, for lead times of about 0–5 days, they provide reliable forecasts of the atmospheric circulation that encompasses the sub-scale processes leading to extremes. Hence, forecasts of extreme events can only be...

The ECHAM 3.2 (T21), ECHAM 4 (T30) and LMD (version 6, grid-point resolution with 96 longitudes × 72 latitudes) atmospheric general circulation models were integrated through the period 1961 to 1993 forced with the same observed Sea Surface Temperatures (SSTs) as compiled at the Hadley Centre. Three runs were made for each model starting from diffe...

The spatial variability of wind gusts is probably as large as that of precipitation, but the observational weather station network is much less dense. The lack of an area-wide observational analysis hampers the forecast verification of wind gust warnings. This article develops and compares several approaches to derive a probabilistic analysis of wi...

This study assesses the detectability of external influences in changes of precipitation extremes in the 20th century, which is explored through a perfect model analysis with an ensemble of coupled climate model simulations. Three indices of precipitation extremes are defined from the generalized extreme value (GEV) distribution and time variations...

Although present day weather forecast models usually cannot provide realistic descriptions of local and particularly extreme weather conditions, they provide reliable forecasts of the atmospheric circulation that encompasses the sub-scale processes leading to extremes. Hence, forecasts of extreme events can only be achieved through a combination of...

This study assesses the detectability of external influences in changes of precipitation extremes in the twentieth century, which is explored through a perfect model analysis with an ensemble of coupled global climate model (GCM) simulations. Three indices of precipitation extremes are defined from the generalized extreme value (GEV) distribution:...

The priority program 'Quantitative Precipitation Forecast' funded by the German Research Foundation (DFG) has been implemented in April 2004 for a period of six years. Within this program observations from almost 1000 rain gauges, which are not routinely used, have been collecting since 2007. Therefore a quality control of this observed raw data is...

Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random variables. One approach to this problem is the use of copulas, which have become popular over recent years, especially in fields like econometrics, finance...

Commonly, postprocessing techniques are employed to calibrate a model forecast. Here, a probabilistic postprocessor is presented that provides calibrated probability and quantile forecasts of precipitation on the local scale. The forecasts are based on large-scale circulation patterns of the 12-h forecast from the NCEP high-resolution Global Foreca...

The sensitivity of climate phenomena in the low latitudes to enhanced greenhouse conditions is a scientific issue of high relevance to billions of people in the poorest countries of the globe. So far, most studies dealt with individual model results. In the present analysis, we refer to 79 coupled ocean–atmosphere simulations from 12 different clim...

A statistical downscaling approach for extremes using censored quantile regression is presented. Conditional quantiles of station data (e.g., daily precipitation sums) in Germany are estimated by means of the large-scale circulation as represented by the NCEP reanalysis data. It is shown that a mixed discrete-continuous response variable, such as a...

A 15 member ensemble of 20th century simulations using the ECHAM4–T42 atmospheric GCM is utilized to investigate the potential predictability of interannual variations of seasonal rainfall over Africa. Common boundary conditions are the global sea surface temperatures (SST) and sea ice extent. A canonical correlation analysis (CCA) between observed...

This chapter presents an overview of some typical meteorological extreme events. For reasons of conciseness we restrict ourselves to wind and precipitation extremes. The major goal is to emphasize the fact that very different types of wind or precipitation extremes may occur on different scales in space and time. The main phenomenological presentat...

A 1000-yr integration of a coupled ocean atmosphere model (ECHO-G) has been analyzed to describe decadal to multidecadal variability in equatorial Pacific sea surface temperature (SST) and thermocline depth (Z20), and their relationship to decadal modulations of El Niño Southern Oscillation (ENSO) behavior. Although the coupled model is characteriz...

The main goal of this study is to determine the oceanic regions corresponding to variability in African rainfall and seasonal differences in the atmospheric teleconnections. Canonical correlation analysis (CCA) has been applied in order to extract the dominant patterns of linear covariability. An ensemble of six simulations with the global atmosphe...

To estimate the potential seasonal predictability of the Euro‐Atlantic atmospheric variability, canonical correlation analysis is used, and a comparison is made between the NCEP reanalysis with ensemble simulations of ECHAM4‐T42 forced with observed sea surface temperature (SST) and sea‐ice boundaries for 1951–94 and changing CO 2 concentration. Th...

To estimate the potential seasonal predictability of the Euro-Atlantic atmospheric variability, canonical correlation analysis is used, and a comparison is made between the NCEP reanalysis with ensemble simulations of ECHAM4-T42 forced with observed sea surface temperature (SST) and sea-ice boundaries for 1951–94 and changing CO2 concentration. The...

A 1000 year integration of a coupled ocean/atmosphere model (ECHO-G) has been analyzed to describe decadal to multi-decadal variability in equatorial Pacific sea surface temperature (SST) and thermocline depth (Z20), and their relationship to decadal modulations of ENSO (El Niño-Southern Oscillation) behavior. Although the coupled model is characte...

One of the leading modes of rainfall variability over West Afrika describes a dipole pattern between the Guinea coastal area upto 10^oN and the Sudan-Sahel zone to the north. Frequently, the Sahel is characterized by dryer than normal conditions, when the rainy season to the south is abundant, and vice versa. This gradient of freshwater input, when...

To encourage the use of the standard parametric test procedures in canonical correlation analysis, the tests are applied to investigate the influence of northern Atlantic SST on the Euro-Atlantic atmospheric circulation.A comparison with a Monte Carlo testing procedure shows that the parametric tests perform properly given that at least one of the...

Recent studies of observational data suggest that Sea Surface Temperature (SST) anomalies in the Atlantic Ocean have a significant influence on the atmospheric circulation in the Atlantic-European sector in early winter and in spring. After reviewing this work and showing that the spring signal is part of a global air-sea interaction, we analyze fo...

The ocean-atmosphere interactions of sea surface temperature and the North Atlantic Oscillation as an atmospheric phenomenon are examined in an ensemble of climate change simulations. The principal task concentrates on the common climate change signals, the lead-lag relationship, the time-space covariability, and the aspect of predictability. The s...

The ECHAM 3.2 (T21), ECHAM 4 (T30) and LMD (version 6, grid-point resolution with 96 longitudes × 72 latitudes) atmospheric general circulation models were integrated through the period 1961 to 1993 forced with the same observed Sea Surface Temperatures (SSTs) as compiled at the Hadley Centre. Three runs were made for each model starting from diffe...

We present a nowcasting approach for extreme weather events that communicates a probabilistic forecast in terms of quantiles. Furthermore, a new validation score for quantile forecasts, namely the quantile verification (QV) skill score, is introduced. It applies to quantile forecasts for continuous as well as mixed-discrete continuous variables (i....

Our study aims at identifying the interannual to decadal predictability of the Euro- Atlantic atmospheric variability by comparing the NCEP reanalysis with ECHAM4- T42 ensemble simulations forced with observed sea surface temperature (SST) and sea-ice boundaries (GISST2.2) for 1951-1994. To identify those observational patterns of variability that...

Anderungen im Extremwertverhalten realer Klimasysteme statistisch belastbar aus Kli- masimulationen abschatzen zu konnen, ist es zunachst notwendig, diese bezuglich extremer Er- eignisse zu validieren. Wir untersuchen eine Ensemble von Simulationen mit dem gekoppelten Klimamodell ECHO-G. Innerhalb dieses Ensembles werden die Treibhausgas- und Aeros...