Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limitedarea numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.

Abstract. This study presents a detailed analysis of the climatological distribution of precipitation in relation to cyclones and fronts over Europe for the 9-year period 2000–2008. The analysis uses hourly output of a COSMO (Consortium for Small-scale Modeling) model simulation with 2.2 km grid spacing and resolved deep convection. Cyclones and fronts are identified as two-dimensional features in 850 hPa geopotential, equivalent potential temperature, and wind fields and subsequently tracked over time based on feature overlap and size. Thermal heat lows and local thermal fronts are removed based on track properties. This dataset then serves to define seven mutually exclusive precipitation components: cyclonic (near cyclone center), cold-frontal, warm-frontal, collocated (e.g., occlusion area), far-frontal, high-pressure (e.g., summer convection), and residual. The approach is illustrated with two case studies with contrasting precipitation characteristics. The climatological analysis for the 9-year period shows that frontal precipitation peaks in winter and fall over the eastern North Atlantic and the Alps (> 70 % in winter), where cold frontal precipitation is also crucial year-round; cyclonic precipitation is largest over the North Atlantic (especially in summer with > 40 %) and in the northern Mediterranean (widespread > 40 %); high-pressure precipitation occurs almost exclusively over land and primarily in summer (widespread 30 %–60 %, locally >80 %); and the residual contributions uniformly amount to about 20 % in all seasons. Considering heavy precipitation events (defined based on the local 99.9th all-hour percentile) reveals that high-pressure precipitation dominates in summer over the continent (50 %–70 %, locally >80 %); cold fronts produce much more heavy precipitation than warm fronts; and cyclones contribute substantially (50 %–70 %), especially in the Mediterranean in fall through spring and in northern Europe in summer.

Abstract. This study presents a detailed analysis of the climatological distribution of precipitation in relation to cyclones and fronts over Europe for the nine-year period 2000–2008. The analysis uses hourly output of a COSMO (Consortium for Small-scale Modeling) model simulation with 2.2 km grid spacing and resolved deep convection. Cyclones and fronts are identified as two-dimensional features in 850 hPa geopotential, equivalent potential temperature, and wind fields, and subsequently tracked over time based on feature overlap and size. Thermal heat lows and local thermal fronts are removed based on track properties. This data set then serves to define seven mutually exclusive precipitation components: high-pressure (e.g., summer convection), cyclonic (near cyclone center), cold-frontal, warm-frontal, collocated (e.g., occlusion area), far-frontal, and residual. The approach is illustrated with two case studies with contrasting precipitation characteristics. The climatological analysis for the nine-year period shows that frontal precipitation peaks in fall and winter over the eastern North Atlantic, with cold frontal precipitation also being crucial year-round near the Alps; cyclonic precipitation is largest over the North Atlantic (especially in summer) and in the northern Mediterranean (except in summer); high-pressure precipitation occurs almost exclusively over land and primarily in summer; and the residual contributions uniformly amount to about 20 % in all seasons. Considering heavy precipitation events (defined based on the local 99.9th percentile) reveals that high-pressure precipitation dominates in summer over the continent; cold fronts produce much more heavy precipitation than warm fronts; and cyclones contribute substantially, especially in the Mediterranean in fall through spring and in Northern Europe in summer.

Potential vorticity (PV) is a quantity that can be computed by combining the rotation and stratification in the atmosphere. Due to the combination of these physical processes potential vorticity is considered as one of the most important scalar quantities in atmospheric dynamics. It is able to explain the occurrence of frontal rain bands and plays a key role in particularly strong wind peaks in extratropical cyclones. When wind flows around mountain peaks, rather than over it, a potential vorticity accumulation shaped as elongated banners forms in the mountain's lee. The role of these so called potential vorticity banners has recently raised considerable interest in the meteorological community for instance due to their influence in aviation wind hazards and maritime transport. I thankfully look back at a great experience while working on this Thesis. I particularly want to thank my supervisor Dr. Tobias Günther who supported me while I was working on this Master Thesis. I am very grateful to Tobias's challenging questions and valuable advise which played a central role to complete this work. I learned a lot from our respectful, open and friendly interactions we had.