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Air-sea feedbacks between the Mediterranean Sea and the atmosphere on various temporal and spatial scales play a major role in the Mediterranean regional climate system and beyond. The Mediterranean Sea is a source of moisture due to excess evaporation and, on a long-term average, is associated with a warming of the lower atmosphere in contact with the sea surface due to heat loss at the air-sea interface. The complex air-sea interactions and feedbacks in the Mediterranean basin strongly modulate the sea surface fluxes and favor several cyclogenetic activities under certain meteorological conditions. Examples of such cyclonic activities are medicanes (Mediterranean hurricanes) and Vb-cyclones. Medicanes are mesoscale, marine, and warm-core Mediterranean cyclones that exhibit some similarities to tropical cyclones, while Vb-cyclones are extra-tropical cyclones, that propagate from the Western Mediterranean Sea and travel across the Eastern European Alps into the Central European region. Extremely strong winds and heavy precipitation associated with these cyclones can lead to severe destruction and flooding. Changes in the intensity and frequency of these cyclones are also projected under changing future climate conditions, where the Mediterranean region has been identified as a hotspot in terms of rising temperatures.
The development of high-resolution regional climate models (RCMs) has progressed our understanding of the processes characterizing the Mediterranean climate. However, large uncertainties still exist regarding the estimates of air-sea fluxes, which, in turn, affect the simulation of the Mediterranean climate. Several factors can be attributed to such discrepancies, such as data quality, temporal and spatial resolution, and the misrepresentation of physical processes. To overcome some of these inconsistencies and deficiencies of the existing climate simulations, a new high-resolution atmosphere-ocean regional coupled model (AORCM) has been developed to simulate the air-sea feedback mechanisms. This coupled model incorporates the coupling of RCM COSMO-CLM (CCLM) and the regional ocean model NEMO-MED12 for the Mediterranean Sea (MED) as well as NEMO-NORDIC for the North- and Baltic Sea (NORDIC). Several experiments were performed using both the coupled and uncoupled models to investigate the impact of air-sea interactions and feedbacks on sea surface heat fluxes, wind speed, and on the formation of Mediterranean cyclones (i.e., medicanes and Vb-cyclones). These experiments were performed using different horizontal atmospheric grid resolutions to analyze the effect of resolution on sea surface heat fluxes, wind speed, and the development of medicanes.
The results of the present study indicate that a finer atmospheric grid resolution ([is as appreciated as]9 vs. [is as appreciated as]50 km) improved the wind speed simulations (particularly near coastal areas) and subsequently improved the simulations of the turbulent heat fluxes. Both parameters were better simulated in the coupled simulations than in the uncoupled simulations, but coupling introduced a warm SST bias in winter. Radiation fluxes were slightly better represented in coarse-grid simulations than in fine-grid simulations. However, the higher-resolution coupled model could reproduce the observed net outgoing total surface heat flux over the Mediterranean Sea. In addition to that sub diurnal SST variations have a strong effect on sub-daily heat fluxes and wind speed but minor effects at longer timescales. Regarding the impact of atmospheric grid resolution ([is as appreciated as]50, 25, and [is as appreciated as]9 km) and ocean coupling on medicanes, it was detected that the coupled model with a finer atmospheric grid ([is as appreciated as]9 km) was able to not only reproduce most medicane events, but also improved the track length, warm core, and wind speed compared to the uncoupled model. The coupled model with the coarse-grid ([is as appreciated as]50 and [is as appreciated as]25 km) did not show any improvement in simulating medicanes compared to the uncoupled model. The spectral nudging technique, applied on the wind components above 850 hPa in the interior domain to keep large-scale circulation close to the driving data (i.e., ERAInterim reanalysis), improved the accuracy of the times and locations of generated medicanes, but no improvement was found in the track length and intensity.
Concerning the role of the Mediterranean Sea coupling on Vb cyclones, the investigation showed that atmosphere-ocean coupling had an overall positive impact, although with a strong case-by-case variation, on the trajectories and intensity of Vb-cyclones as a result of the variation in moisture source for each event. In general, all model configurations could replicate Vbcyclones, their trajectories, and associated precipitation fields. The average structure of the precipitation field was best represented in the coupled simulations. Coupling of the North- and Baltic Seas also showed an improvement in some of the simulated Vb-cyclones.
The atmosphere-ocean coupling showed an overall positive impact on the simulation of sea surface heat fluxes and Mediterranean cyclones (medicanes and Vb-cyclones). Moreover, the representation of sea surface heat fluxes, wind speed, and medicane features was more realistic when using a finer atmospheric grid resolution (less than 10 km). The present study suggests that the combination of a finer atmospheric grid resolution together with atmosphere-ocean coupling is advantageous in simulating the Mediterranean climate system.
The main objective of this PhD work is to assess the impact of fine-scale air-sea interaction on the performance of a regional climate prediction model in marginal sea regions. Focus is on the North and Baltic Seas, the largest marginal sea area in the mid-latitudes. Motivation for this work is to better understand the interaction between the different components of the climate system, namely atmosphere, ocean and sea-ice. In addition to that, the sea regions of interest, the North and Baltic Seas, are orographically complex and cannot be resolved by a global ocean model. The ice coverage on the Baltic Sea is underestimated in the stand-alone atmospheric model COSMO-CLM due to the low water freezing temperature value assumed, which is not applicable for such brackish water body. To fulfil the thesis goal, a new regional coupled atmosphere-ocean-ice system was developed for these two seas, named COSMO-CLM/NEMO. The two-way coupling system involves active feedback from both component models: the limited-area climate model COSMO-CLM and the regional ocean model NEMO-NORDIC.
The coupled system COSMO-CLM/NEMO for the North and Baltic Seas was used to study the impact of sea surface temperature and sea ice on the atmosphere on diffrent topics. The long term impact of the North and Baltic Seas was studied through 15- year long simulations driven by European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Furthermore, to see whether the marginal sea modelling can advance the simulation of extreme climate events, the coupled model was used to reproduce six extreme snowband phenomena over the Baltic Sea in simulations driven by ERA-interim data. Last but not least, the role of the North and Baltic Sea model in improving long-term regional climate prediction was examined. Two sets of experiments with coupled and uncoupled models, each set has five independent decadal hindcasts forced by global climate model, were carried out.
All results were compared with observations and the stand-alone atmospheric model COSMO-CLM results. In all experiments, COSMO-CLM/NEMO showed good agreement with observations. Improvements compared with the uncoupled COSMO-CLM were also found. Coupling was found to affect the air temperature not only around the coupled sea region but also inland. The convective snowbands over the Baltic Sea were successfully reproduced by the coupled model. The high contrast of temperature in the air column, as well as considerably high amounts of surface heat fluxes exchanged between air and sea could not be simulated by COSMO-CLM without the help of reanalysis data. The coupled model also provided better forecasts in decadal scales compared with the uncoupled model and the global model. The added predictability came from the initialized regional seas and better simulated sea surface temperatures by the ocean model.
The impact of the North and Baltic Seas on the climate of the surrounding regions is in certain phases dominated by the North Atlantic Oscillation (NAO) activity. In this thesis, the relation between the NAO and the marginal sea influences was studied. It is confirmed by this study that, in strong phases, the NAO can overpower the impact of the local seas. During dominant phases of NAO, the European climate is mainly governed by large-scale circulation. On the other hand, the local seas play an important role in determining the European climate when NAO is in weak phases.
The added value of the coupled model raises promising perspectives for research in this field. It points to a potential benefit of using the coupled atmosphere-ocean-ice system for climate prediction in the region surrounding the North and Baltic Seas. Along with that, it is still a challenge to complete the model representation of the climate system by adding more climate components (such as a hydrological model). Further improvement of the coupled system can be achieved by coupling for a larger sea region, or by trying to reduce remaining low performance of the coupled model in some areas with a better configuration of the current system.
In dieser Dissertation wird die Parametrisierung von subgitterskaligen (SGS) Prozessen in Atmosphärenmodellen untersucht. Die Arbeit befasst sich mit den stochastisch angetriebenen Flachwassergleichungen, im ersten Teil in einer räumlichen Dimension und im zweiten Teil in zwei Dimensionen. Die Einteilung in aufgelöste und SGS-Variable erfolgt in beiden Fällen über lokale räumliche Mittel der Ursprungsvariable und deren Abweichungen vom lokalen Mittel.
Im eindimensionalen Fall liegt zwischen den Variablen eine deutliche Separation der charakteristischen Zeitskalen vor, wodurch die Anwendung der stochastischen Moden Reduktion (SMR) ermöglicht wird. Die SMR generiert ein reduziertes Modell der aufgelösten Variable mit einer stochastischen SGS-Parametrisierung, im Folgenden auch Schließung genannt. Die SMR-Schließung basiert auf den Grundgleichungen des Flachwassermodells und ist numerisch effizient einsetzbar, da sie nur eine geringe Anzahl von benachbarten Zellen koppelt. Sie verbessert die Ergebnisse des reduzierten Modells und übertrifft die Ergebnisse zweier zum Vergleich untersuchter empirischer stochastischer Schließungen. Den größten Zugewinn liefert sie im Energiespektrum, insbesondere für kleine Skalen. Das Ergebnis der SMR-Schließung kann verbessert werden, indem die Amplitude der stochastischen Schließungskomponente gedämpft wird. Die SMR-Schließung ist skalenabhängig im Sinne der räumlichen Modellauflösung. Untersucht wird die Schließung bei Halbierung und Viertelung der räumlichen Auflösung, wo sie ihre Überlegenheit gegenüber den empirischen Schließungen wiederholt bestätigt.
Im Unterschied zum eindimensionalen Fall ist in zwei Dimensionen auch die Corioliskraft enthalten und eine räumliche Divergenz der Schwerewellen möglich. Zwischen der aufgelösten und der SGS-Variable kommt es erneut zu einer Separation der charakteristischen Zeitskalen. Die Separation ist allerdings weniger stark ausgeprägt als im eindimensionalen Fall. Grund hierfür ist das Auftreten einer lang korrelierten geostrophisch balancierten Mode, welche auch auf die SGS-Variable projiziert. Das Vorgehen zur Bestimmung der SMR-Schließung für das zweidimensionale Modell verläuft analog zum eindimensionalen Fall. Es werden die Ergebnisse des hoch aufgelösten Referenzmodells und zweier Modelle ohne SGS-Schließung verglichen.