Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
28
result(s) for
"Frauen, Claudia"
Sort by:
Girls in pearls : the story of a passion in paintings and photographs
A collection of paintings, drawings, prints and photographs of noble women, imperial princesses, society ladies and Hollywood divas wearing their finest pearl tiaras, necklaces, brooches and earrings. Commentaries explain the context in which each image was created.
Book
Influences of the tropical Indian and Atlantic Oceans on the predictability of ENSO
The El Niño Southern Oscillation (ENSO) is the leading mode of climate variability and predictable on interannual time scales. Recent studies suggest that the tropical Indian and Atlantic Oceans influence the dynamics and predictability of ENSO. Here we investigate these effects in a hybrid coupled model consisting of a full complexity atmospheric general circulation model (GCM) coupled to a strongly simplified linear 2‐dimensional ENSO recharge oscillator ocean model. We find that the tropical Indian and Atlantic Oceans have distinct effects on the dynamics and predictability. The decoupling of the tropical Indian Ocean has a strong impact onto ENSO dynamics, but the initial conditions of it have only a small impact on the ENSO predictability. In contrast, initial conditions of the tropical Atlantic have a stronger impact on the predictability of ENSO, but the decoupling of the tropical Atlantic has almost no effect on the ENSO dynamics. Key Points Tropical Indian and Atlantic Oceans influence ENSO Indian Ocean has strong impact on dynamical aspects of ENSO Tropical Atlantic Ocean has strong influence on ENSO predictability
Journal Article
El Niño and La Niña amplitude asymmetry caused by atmospheric feedbacks
Interannual variability of tropical Pacific sea surface temperatures (SST) has an asymmetry with stronger positive events, El Niño, and weaker negative events, La Niña, which is generally attributed to processes in the ocean. Here we present evidence from a new hybrid coupled model that the asymmetry and seasonality of El Niño can be caused by nonlinear and seasonally varying atmospheric feedbacks. The model consists of the ECHAM5 global atmospheric general circulation model (GCM) coupled to the 2‐dimensional El Niño linear recharge oscillator ocean model in the tropical Pacific and a mixed layer ocean elsewhere. Despite the models simplistic and, by construction, linear representation of the ocean dynamics, it is able to simulate the main statistical features of El Niño including period, seasonality, skewness, and kurtosis. Analyses of the model show that a nonlinear relationship between zonal wind stress and SST is causing the El Niño‐La Niña asymmetry.
Journal Article
Analysis of the Nonlinearity of El Niño–Southern Oscillation Teleconnections
El Niño–Southern Oscillation (ENSO) has significant variations and nonlinearities in its pattern and strength. ENSO events vary in their position along the equator, with some located in the central Pacific (CP) and others in the east Pacific (EP). To study how these variations are reflected in global ENSO teleconnections, both observations and idealized atmospheric general circulation model (AGCM) simulations are analyzed. Clear nonlinearities exist in observed teleconnections of sea level pressure (SLP) and precipitation. However, it is difficult to distinguish if these are caused by the different signs, strengths, or spatial patterns of events (strong El Niño events mostly being EP events and strong La Niña events mostly being CP events) or by combinations of these. Therefore, sensitivity experiments are performed with an AGCM forced with idealized EP and CP ENSO sea surface temperature (SST) patterns with varying signs and strengths. The response is generally stronger for warm events than for cold events and the teleconnection patterns vary with changing SST anomaly patterns. EP events show stronger nonlinearities than CP events. The nonlinear responses to ENSO events can be explained as a combination of nonlinear responses to a linear ENSO (fixed pattern but varying signs and strengths) and a linear response to a nonlinear ENSO (varying patterns). Any observed event is a combination of these aspects. While in most tropical regions these add up, leading to stronger nonlinear responses than expected from the single components, in some regions they cancel each other, resulting in little overall nonlinearity. This leads to strong regional differences in ENSO teleconnections.
Journal Article
Analysis of the non-linearity in the pattern and time evolution of El Niño southern oscillation
In this study the observed non-linearity in the spatial pattern and time evolution of El Niño Southern Oscillation (ENSO) events is analyzed. It is shown that ENSO skewness is not only a characteristic of the amplitude of events (El Niños being stronger than La Niñas) but also of the spatial pattern and time evolution. It is demonstrated that these non-linearities can be related to the non-linear response of the zonal winds to sea surface temperature (SST) anomalies. It is shown in observations as well as in coupled model simulations that significant differences in the spatial pattern between positive (El Niño) versus negative (La Niña) and strong versus weak events exist, which is mostly describing the difference between central and east Pacific events. Central Pacific events tend to be weak El Niño or strong La Niña events. In turn east Pacific events tend to be strong El Niño or weak La Niña events. A rotation of the two leading empirical orthogonal function modes illustrates that for both El Niño and La Niña extreme events are more likely than expected from a normal distribution. The Bjerknes feedbacks and time evolution of strong ENSO events in observations as well as in coupled model simulations also show strong asymmetries, with strong El Niños being forced more strongly by zonal wind than by thermocline depth anomalies and are followed by La Niña events. In turn strong La Niña events are preceded by El Niño events and are more strongly forced by thermocline depth anomalies than by wind anomalies. Further, the zonal wind response to sea surface temperature anomalies during strong El Niño events is stronger and shifted to the east relative to strong La Niña events, supporting the eastward shifted El Niño pattern and the asymmetric time evolution. Based on the simplified hybrid coupled RECHOZ model of ENSO it can be shown that the non-linear zonal wind response to SST anomalies causes the asymmetric forcings of ENSO events. This also implies that strong El Niños are mostly wind driven and less predictable and strong La Niñas are mostly thermocline depth driven and better predictable, which is demonstrated by a set of 100 perfect model forecast ensembles.
Journal Article
The Atlantic Multidecadal Oscillation controls the impact of the North Atlantic Oscillation on North European climate
European climate is heavily influenced by the North Atlantic Oscillation (NAO). However, the spatial structure of the NAO is varying with time, affecting its regional importance. By analyzing an 850-year global climate model simulation of the last millennium it is shown that the variations in the spatial structure of the NAO can be linked to the Atlantic Multidecadal Oscillation (AMO). The AMO changes the zonal position of the NAO centers of action, moving them closer to Europe or North America. During AMO+ states, the Icelandic Low moves further towards North America while the Azores High moves further towards Europe and vice versa for AMO- states. The results of a regional downscaling for the East Atlantic/European domain show that AMO-induced changes in the spatial structure of the NAO reduce or enhance its influence on regional climate variables of the Baltic Sea such as sea surface temperature, ice extent, or river runoff.
Journal Article
Role of wind stress in driving SST biases in the tropical Atlantic
Coupled climate models used for long-term future climate projections and seasonal or decadal predictions share a systematic and persistent warm sea surface temperature (SST) bias in the tropical Atlantic. This study attempts to better understand the physical mechanisms responsible for the development of systematic biases in the tropical Atlantic using the so-called Transpose-CMIP protocol in a multi-model context. Six global climate models have been used to perform seasonal forecasts starting both in May and February over the period 2000–2009. In all models, the growth of SST biases is rapid. Significant biases are seen in the first month of forecast and, by 6 months, the root-mean-square SST bias is 80% of the climatological bias. These control experiments show that the equatorial warm SST bias is not driven by surface heat flux biases in all models, whereas in the south-eastern Atlantic the solar heat flux could explain the setup of an initial warm bias in the first few days. A set of sensitivity experiments with prescribed wind stress confirm the leading role of wind stress biases in driving the equatorial SST bias, even if the amplitude of the SST bias is model dependent. A reduced SST bias leads to a reduced precipitation bias locally, but there is no robust remote effect on West African Monsoon rainfall. Over the south-eastern part of the basin, local wind biases tend to have an impact on the local SST bias (except in the high resolution model). However, there is also a non-local effect of equatorial wind correction in two models. This can be explained by sub-surface advection of water from the equator, which is colder when the bias in equatorial wind stress is corrected. In terms of variability, it is also shown that improving the mean state in the equatorial Atlantic leads to a beneficial intensification of the Bjerknes feedback loop. In conclusion, we show a robust effect of wind stress biases on tropical mean climate and variability in multiple climate models.
Journal Article
Long-Term Mean Circulation of the Baltic Sea as Represented by Various Ocean Circulation Models
The skill of the state-of-the-art ocean circulation models GETM (General Estuarine Transport Model), RCO (Rossby Centre Ocean model), and MOM (Modular Ocean Model) to represent hydrographic conditions and the mean circulation of the Baltic Sea is investigated. The study contains an assessment of vertical temperature and salinity profiles as well as various statistical time series analyses of temperature and salinity for different depths at specific representative monitoring stations. Simulation results for 1970-1999 are compared to observations from the Baltic Environmental Database (BED). Further, we analyze current velocities and volume transports both in the horizontal plane and through three transects in the Baltic Sea. Simulated current velocities are validated against ten years of Acoustic Doppler Current Profiler (ADCP) measurements in the Arkona Basin and five years of mooring observations in the Gotland Basin. Furthermore, the atmospheric forcing datasets, which drive the models, are evaluated using wind measurements from 28 automatic stations along the Swedish coast. We found that the seasonal cycle, variability, and vertical profiles of temperature and salinity are simulated close to observations by RCO with an assimilation setup. All models reproduce temperature well near the sea surface. Salinity simulations are of lower quality from GETM in the northern Baltic Sea and from MOM at various stations. Simulated current velocities lie mainly within the standard deviation of the measurements at the two monitoring stations. However, sea surface currents and transports in the ocean interior are significantly larger in GETM than in the other models. Although simulated hydrographic profiles agree predominantly well with observations, the mean circulation differs considerably between the models highlighting the need for additional long-term current measurements to assess the mean circulation in ocean models. With the help of reanalysis data ocean state estimates of regions and time periods without observations are improved. However, due to the lack of current measurements only the baroclinic velocities of the reanalyses are reliable. A substantial part of the differences in barotropic velocities between the three ocean models and reanalysis data is explained by differences in wind velocities of the atmospheric forcing datasets.
Journal Article
Assessment of Eutrophication Abatement Scenarios for the Baltic Sea by Multi-Model Ensemble Simulations
To assess the impact of the implementation of the Baltic Sea Action Plan (BSAP) on the future environmental status of the Baltic Sea, already available uncoordinated multi-model ensemble simulations for the Baltic Sea region for the 21st century were analyzed. The scenario simulations were driven by regionalized global general circulation model (GCM) data using several regional climate system models and forced by various future greenhouse gas emission and air- and river-borne nutrient load scenarios following either reference conditions or the BSAP. To estimate uncertainties in projections, the largest ever multi-model ensemble for the Baltic Sea comprising 58 transient simulations for the 21st century was assessed. Data from already existing simulations from different projects including regionalized GCM simulations of the third and fourth assessment reports of the Intergovernmental Panel on Climate Change based on the corresponding Coupled Model Intercomparison Projects, CMIP3 and CMIP5, were collected. Various strategies to weigh the ensemble members were tested and the results for ensemble mean changes between future and present climates are shown to be robust with respect to the chosen metric. Although (1) the model simulations during the historical period are of different quality and (2) the assumptions on nutrient load levels during present and future periods differ between models considerably, the ensemble mean changes in biogeochemical variables in the Baltic proper with respect to nutrient load reductions are similar between the entire ensemble and a subset consisting only of the most reliable simulations. Despite the large spread in projections, the implementation of the BSAP will lead to a significant improvement of the environmental status of the Baltic Sea according to both weighted and unweighted ensembles. The results emphasize the need for investigating ensembles with many members and rigorous assessments of models’ performance.
Journal Article
Assessment of Uncertainties in Scenario Simulations of Biogeochemical Cycles in the Baltic Sea
Following earlier regional assessment studies, such as the Assessment of Climate Change for the Baltic Sea Basin and the North Sea Region Climate Change Assessment, knowledge from available literature about future scenario simulations of biogeochemical cycles in the Baltic Sea and their uncertainties is assessed. Uncertainties in these projections are caused by climate model uncertainties (including global and regional models and the experimental setup), by unknown future nutrient load and greenhouse gas emissions (or concentrations) and by natural variability. The determination and reduction of uncertainties of scenario simulations are important issues for marine management. For instance, management would like to know from these coupled climate-environmental projections whether nutrient load abatement strategies such as the Baltic Sea Action Plan (BSAP) will meet its objectives of restored water quality status in future climate or whether additional measures are required. The results of an accompanied multi-model study indicate that the implementation of the BSAP will lead to a significant improvement of the environmental status of the Baltic Sea. However, uncertainties are large and their sources need to be understood to draw conclusions about the effectiveness of measures. Our assessment of sources of uncertainties in projections of biogeochemical cycles suggests that the biggest uncertainties (listed in descending order of importance) are caused by (1) unknown current and future bioavailable nutrient loads from land and atmosphere and the experimental setup (including the spin up strategy), (2) differences between the projections of global and regional climate models, in particular, with respect to the global mean sea level rise and regional water cycle, (3) differing model-specific responses of the simulated biogeochemical cycles to long-term changes in external nutrient loads and climate of the Baltic Sea region, and (4) unknown future greenhouse gas emissions. Regular assessments of the models’ skill (or quality compared to observations) for the Baltic Sea region and the spread in scenario simulations (differences among projected changes) and the improvement of dynamical downscaling methods are recommended.
Journal Article